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首页医源资料库在线期刊美国临床营养学杂志2006年84卷第5期

Secular trends in patterns of self-reported food consumption of adult Americans: NHANES 1971-1975 to NHANES 1999–

来源:《美国临床营养学杂志》
摘要:ABSTRACTBackground:ThecontributorstotrendsinincreasingprevalenceofobesityintheUSpopulationarepoorlyunderstood。Objective:WeexaminedseculartrendsinfoodconsumptionbehaviorstounderstandtheirpossiblecontributiontoincreasingenergyintakesandadiposityintheAmerican......

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Ashima K Kant and Barry I Graubard

1 From the Department of Family, Nutrition, and Exercise Sciences, Queens College of the City University of New York, Flushing, NY (AKK), and the Division of Cancer Epidemiology and Genetics, Biostatistics Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD (BIG)

2 Supported in part by NIH grant DK069413 (AKK) and by the intramural research program of the Department of Health and Human Services, National Institutes of Health, National Cancer Institute (BIG).

3 Reprints not available. Address correspondence to AK Kant, Department of Family, Nutrition, and Exercise Sciences, Remsen Hall, Room 306E, Queens College of the City University of New York, Flushing, NY 11367. E-mail: ashima.kant{at}qc.cuny.edu.


ABSTRACT  
Background: The contributors to trends in increasing prevalence of obesity in the US population are poorly understood.

Objective: We examined secular trends in food consumption behaviors to understand their possible contribution to increasing energy intakes and adiposity in the American population.

Design: We used dietary data from 4 consecutive National Health and Nutrition Examination Surveys (NHANES) to examine trends (1971–2002) in frequency of eating episodes, meal and snack consumption, quantity of food consumed, and the energy density of foods reported by adult Americans (n = 39 094). Logistic and linear regression methods were used to adjust for multiple covariates and survey design.

Results: The reported number of all eating episodes increased slightly in women from 4.90 in 1971–1975 to 5.04 in 1999–2002 (P for trend = 0.002). The amount (in g) of foods and beverages consumed, the energy density of foods, and energy intake per eating episode increased, but the mention of breakfast declined in both sexes (P for trend < 0.0001). The observed trends in mention of a snack (in men) and percentage of energy from evening food intake (in women) were downward. The amount (in g) of foods and their energy density were independent positive correlates of obesity in combined data from all surveys (P for trend < 0.0001).

Conclusions: Our results do not support large increases in eating frequency, snacking, or evening eating by the American population from 1971 to 2002. The quantity of foods and their energy density increased beginning in NHANES III (1988–1994) with trajectories roughly parallel to the rates of prevalence of obesity in the US population. However, we urge cautious interpretation of these results because of concurrent changes in dietary methods during this period.

Key Words: Secular trends • National Health and Nutrition Examination Surveys • NHANES • eating frequency • snack intake • breakfast intake • energy density • evening eating • portion size • energy intake • obesity • body mass index


INTRODUCTION  
Data from recent national surveys indicate a continuation of the trend for increasing prevalence of obesity in the US population (1, 2). Food disappearance and survey data implicate an increase in energy intake without a corresponding increase in energy expenditure as a possible explanation for the persistent positive energy balance and eventually weight gain in the US population (3–5). Multiple factors may be responsible for increasing energy intakes, but they are poorly understood. Many food consumption behaviors, including portion size of foods, number of meals eaten away from home, frequency of eating episodes, temporal distribution of food intake, and energy density of foods, may relate with energy intake (5–16). Because of an expanding food supply, aggressive food marketing, and changes in work and leisure patterns of Americans, it is reasonable to expect a change in some of these food consumption behaviors over the course of the past 3 decades. An examination of changing patterns of food consumption can help in understanding the correlates of increasing energy intake. In this context, trends in away-from-home eating (6, 7), portion sizes of foods (8–11), and snacking (17, 18) have been the subject of recent reports; however, little is known about changes in the other food consumption behaviors mentioned earlier. The objective of this study was to examine secular (time) trends (1971–2002) in food consumption behaviors—as reflected in the frequency of eating episodes, snacking, breakfast consumption, evening eating, the amount of food consumed (in g), and the energy density of foods—of American men and women.


SUBJECTS AND METHODS  
We used data collected in the National Health and Nutrition Examination Survey (NHANES) I (1971–75) (19), II (1976–1980) (20), III (1988–1994) (21), 1999–2000 (22), and 2001–2002 (23), conducted by the National Center for Health Statistics (NCHS) of the Centers for Disease Control and Prevention. Each survey was a stratified, multistage, national probability sample of the civilian noninstitutionalized population of the United States. The subjects surveyed in NHANES I and II were aged 1–74 y, those surveyed in NHANES III were aged 2 mo, and those surveyed in NHANES 1999–2002 were of all ages. Each survey included a household interview of the sample person conducted by a trained interviewer and a health examination in the mobile examination center (MEC). The health examination included a physical examination, a dental examination, radiography, measurements of weight and height, an interview to collect a 24-h dietary recall, and the collection of blood and urine specimens. Survey response rates for MEC-examined persons for NHANES I (19), II (20), III (21), and 1999–2000 (22) were 74%, 73%, 78%, and 78%, respectively.

Dietary methods
All surveys collected dietary information with the use of a 24-h recall administered by a trained dietary interviewer in the MEC (19–23). Dietary interviewers used paper-and-pencil methods in the NHANES I and II, which changed to computer-assisted, automated methods in later surveys. The dietary recalls collected for the NHANES 1999–2000 and 2001 survey years used a computer-assisted dietary interview that included a 4-step multiple pass approach (22, 23). In the NHANES 2002, the dietary data were collected with the use of a 5-step multiple pass approach with dietary recall methods that are part of the integrated US Department of Agriculture and NHANES protocol of What We Eat in America(23).

Analytic sample
For each of the 4 surveys, all nonpregnant, nonlactating respondents aged 25–74 y with a reliable, self-reported 24-h dietary recall and measured height and weight were included in the analytic sample. The upper age cutoff of 74 y was necessary because the NHANES I and II did not include respondents aged >74 y. The final analytic sample comprised 39 094 respondents (NHANES I = 10 537; NHANES II = 10 118, NHANES III = 12 042, and NHANES 1999–2002 = 6397).

Food consumption variables
The food consumption behaviors examined in this study were derived from a 24-h recall as described below. The behaviors examined included frequency of eating episodes, breakfast consumption, snack intake, evening eating, and dietary energy density.

Frequency of eating episodes
Each 24-h recall included information on the time of day (clock time) when foods or beverages were consumed. Using methods we previously reported (15), we determined the frequency of eating episodes from the discrete number of clock times when foods or beverages were consumed in the 24-h recall. One eating episode comprised all foods and beverages consumed at 1 clock time, regardless of the type or the amount of food reported.

Breakfast consumption
In each recall the respondents were asked to identify or name the eating occasion for each reported food and beverage. In the NHANES I and II, for each food item recalled, information was collected on the "ingestion period" (AM, noon, PM, or between meals). For the NHANES III and the NHANES 1999–2002, the subject was asked to name the eating occasion when each food was recalled and included the following choices (breakfast, lunch, dinner, snack, or their equivalents in Spanish). We determined breakfast consumption based on whether the respondent mentioned any foods and beverages for the AM meal or for breakfast, desayuno, or brunch. The resulting variable was expressed as whether breakfast was reported, and the proportion of 24-h energy intake from foods and beverages mentioned in the eating episodes considered as breakfast.

Snack intake
Snack intake was also determined from named eating occasions described above. The number of different clock times at which "between meals" or "snack" were mentioned contributed to snack events. We expressed snacking behavior as whether a snack was reported, number of snacking episodes on the recall day, and percentage of 24-h energy intake from snacks.

Evening eating
We used methods previously reported by us (12, 13) to assess evening eating. Accordingly, all foods and beverages reportedly consumed at or after 1700 until the last reported eating episode were considered to comprise evening eating. Evening eating is expressed as a variable that is the proportion of 24-h energy intake from foods and beverages consumed at or after 1700.

Dietary energy density
No consensus exists about how energy density should be defined (24). The association of different energy density measures with energy intake and body weight varies depending on its definition (24–26). For example, the association of energy intake with energy density variables that included beverages was not as strong as energy density variables that were derived from solid foods (25), possibly because of different physiologic mechanisms for regulation of beverage intake, as suggested by Rolls et al (27). The NHANES dietary data include weight (in g) and the energy content of each food and beverage reported in the 24-h recall. From these data, we assessed dietary energy density (kcal/g) as 2 different measures: 1) overall energy density or energy content of all foods and beverages reported in the 24-h recall [energy from all foods and beverages was divided by the weight (in g) of all foods and beverages], and 2) energy density of all foods and nutritive beverages [energy from all foods and nutritive beverages was divided by the weight (in g) of all foods and nutritive beverages]. Milk and 100% juice were considered as nutritive beverages, and all alcoholic and nonalcoholic energy-yielding or nonenergy-yielding beverages (eg, coffee, tea, sodas, juice drinks) were excluded from this measure. For those reporting breakfast, evening eating, or snacking in the recall, we also computed the energy density of all foods and beverages reported at these eating occasions.

Analytic methods
We used linear or logistic multiple regression models to assess secular trends in food consumption behaviors examined in this study. Although we tested for sex by survey interactions, all primary results are presented stratified by sex. This reflects a priori decisions about sex-specific hypothesis testing because of differences in dietary intakes and prevalence of obesity between men and women. Because of differences in the distribution of several potential factors that may be associated with reporting of food consumption patterns among surveys, the regression models included sex, age, race (white, black, and other), education (<12 y, 12 y, >12 y), day of the recall (Sunday to Monday), smoking status (never, former, current), any leisure-time physical activity (yes, no), body mass index (BMI; in kg/m2) (continuous), self-reported chronic disease (heart disease, diabetes, high blood pressure) (yes, no), and survey (NHANES I, NHANES II, NHANES III, and NHANES 1999–2002), as independent variables with each food consumption behavior as a continuous or binary outcome. Output from linear or logistic multiple regression models was used to calculate the adjusted means or proportions (predictive margins) of food consumption variables (with SEs) for each sex and survey group. This method directly standardized the means to the distribution of the covariates for the combined US populations represented by the weighted NHANES samples (28). We note that results of regression analysis with adjustment for multiple covariates were substantively similar to those obtained in our preliminary analyses with adjustments limited to age, race, and education (data not shown, available from authors). The race or ethnicity categories available in the NHANES 1999–2002 differ markedly from race categories in earlier surveys. The NHANES I and II provide only white, black, and other categories. The NHANES III provides both race- and ethnicity-specific categories. However, in the NHANES 1999–2002, the race of Hispanic participants was not available. For the present analyses we grouped Mexican Americans and other Hispanics with whites in the NHANES 1999–2002. This allowed us to categorize race for all surveys as white, black, and other. Respondents missing information on any covariate were excluded from regression models. In tests for trend across surveys, the 4 surveys from 1971 to 2002 were modeled as an ordinal independent variable.

We examined the association of food consumption variables with energy intake and odds of obesity (BMI 30) by using sex-specific linear and logistic regression models, respectively. These models included age, race, leisure-time physical activity, education, smoking status, chronic disease status, and survey as covariates. Reports have pointed out a high occurrence of low-energy reporting in national survey data (29–32). Higher body weight was shown to be associated with low-energy reporting in several reports (29–32). Whether this reflects a reporting bias or low intakes to manage weight cannot be determined for all surveys examined in this study. However, low-energy reporting is believed to affect the ability to detect association of dietary variables with outcomes such as body weight (33). In an attempt to understand whether low-energy reporting modified the associations of food consumption behaviors with the risk of obesity, we also present results adjusted for the ratio of reported energy intake to calculated energy requirement for basal energy expenditure (BEE) (34). BEE was computed with the use of sex-specific equations recommended by the committee for dietary reference intakes (35). We used a ratio of energy intake to BEE of <1.2 to signify low-energy reporting.

We combined data from 4 surveys for these analyses, and we treated the data from the 4 different surveys as independent samples from different populations for purposes of variance estimation. We weighted the data in our analyses by using the NCHS-assigned survey-specific sample weights so as to produce estimates that represented each population (36). All statistical analyses were adjusted for the sample weights and complex sample design of the NHANES by using SAS callable SUDAAN, version 9.0 (37). All reported P values were 2 sided.


RESULTS  
The characteristics of respondents in the 4 surveys are shown in Table 1. The distribution of all characteristics examined varied across surveys (P 0.002, chi-square test of independence for all variables). The proportion of the population with >12 y of education and never smokers increased, and those reporting <12 y of education, current smoker status, or a ratio of energy intake to BEE <1.2 decreased from NHANES I to NHANES 1999–2002.


View this table:
TABLE 1. Characteristics of survey respondents from National Health and Nutrition Examination Survey (NHANES) I to NHANES 1999–20021

 
Over the 3-decade span of the 4 surveys, the number of eating episodes reported in the 24-h recall increased slightly in women (from 4.9 in NHANES I to 5.04 in NHANES 1999–2002) (P for trend = 0.002) but was unchanged in men (Table 2). Across surveys, the reported amount (in g) of all foods and beverages, total energy intake, and the amount (in g) of food and energy per eating episode increased in both men and women (P for trend < 0.0001).


View this table:
TABLE 2. Number of eating episodes and amount of food self-reported in a 24-h recall from National Health and Nutrition Examination Survey (NHANES) I to NHANES 1999–20001

 
Americans reporting breakfast declined from 89% in NHANES I to 82% in NHANES 1999–2002 (P for trend < 0.0001); however, the mean percentage of 24-h energy intake from breakfast declined only in men (Table 3). The percentage of energy from evening food intake declined slightly in women but was unchanged in men. Among men, the percentage reporting a snack and the number of snacking episodes decreased from 1971–75 to 1999–2002 (P for trend < 0.0001); these snack behaviors were unchanged in women. However, the percentage of daily energy from snacks remained unchanged in men and increased slightly in women (P for trend = 0.007). Among snack reporters, although the amount (in g) of foods and beverages reported per snacking episode did not change from 1971 to 2002, the amount of energy consumed per snacking episode increased in both men and women (P for trend < 0.0001).


View this table:
TABLE 3. Meal and snack consumption self-reported in a 24-h recall from National Health and Nutrition Examination Survey (NHANES) I to NHANES 1999–20021

 
The energy density (in kcal/g) of all foods and beverages reported in the recall increased in women but declined slightly in men (Table 4). The energy density (in kcal/g) of foods and nutritive beverages increased over the period of the 4 surveys in both men and women (P for trend < 0.0001). The energy density of all foods and beverages reported as snack, breakfast, or evening intake increased across surveys (P for trend < 0.0001). The sex differences in mean energy density of foods and beverages reported for breakfast or evening were present in earlier surveys but not in 1999–2002 (sex by survey interaction, P < 0.05).


View this table:
TABLE 4. Energy density of self-reported dietary components in a 24-h recall from National Health and Nutrition Examination Survey (NHANES) I to NHANES 1999–20021

 
The number of eating and snack episodes, mention of breakfast or a snack, and the amount (in g) of foods and beverages and their energy density were significant independent predictors of higher energy intake in both men and women [P < 0.0001 for all variables, except mention of breakfast in women (P = 0.02)] (data not shown). Shown in Table 5 is the regression coefficient (ß ± SE) associated with each food consumption variable with obesity (BMI 30) as outcome, from logistic regression models with and without adjustment for low-energy reporting for all surveys combined. The interaction of sex and each food consumption variable (except mention of breakfast) for predicting obesity was not significant (P > 0.05). The inverse association of the number of eating and snacking episodes with likelihood of obesity was not significant after adjustment for low-energy reporting in both sexes. With adjustment for low-energy reporting status, the reported amount (in g) of foods and beverages predicted obesity in all surveys combined (P 0.001). For all surveys combined, the energy density of foods and nutritive beverages was a positive correlate of obesity irrespective of energy reporting status. The association of obesity with the amount (in g) of food intake and energy density of foods and nutritive beverages–adjusted for low-energy reporting status–was also significant in each individual survey (except energy density in NHANES I) (data not shown).


View this table:
TABLE 5. The association of food consumption patterns with BMI 30 from the National Health and Nutrition Examination Survey (NHANES) I to NHANES 1999–20021

 

DISCUSSION  
The results of this study suggest relatively small shifts in patterns of food consumption over the past 3 decades. These results are contrary to our expectation of a population-wide increase in frequency of eating as a result of an increase in the "grazing" type of food consumption behaviors. Instead, our results suggest an increase in the quantity and energy density of foods over the past 3 decades. It is not surprising, therefore, that the quantity of food and the energy intake per eating episode were higher in later surveys relative to earlier ones.

To our knowledge, no published reports are available of secular trends in overall eating frequency or energy density of self-reported American diets. In our study, little change in amounts (in g) reported or energy density was apparent from 1971 to 1980; increases in amounts or energy density first appeared in the NHANES III (1988–1994), and a further increase occurred in the NHANES 1999–2002. These trends roughly parallel the trends in increasing prevalence of adiposity first noted in NHANES III and subsequent surveys relative to the NHANES I and II (1, 2). Although, given these trajectories, it is tempting to speculate that the amount (in g) and energy density of foods may have contributed to the trend for increasing body weight (Figure 1), methodologic limitations (discussion to follow) temper the possible conclusions. Our finding of a positive trend for amounts of foods and beverages reported is consistent with other reports of an increase in portion sizes of foods reported in US surveys (9, 10). Rolls et al (38) have shown that higher portion sizes increased energy intake irrespective of body weight in both men and women. Furthermore, the effects of portion size and energy density on energy intake were additive (39).


View larger version (15K):
FIGURE 1.. Secular trends (1971–2002) in adjusted mean (±SE) energy density of foods and nutritive beverages, and amount of all foods and beverages, and the prevalence of obesity (BMI 30) in the US population. Data are from National Health and Nutrition Examination Survey (NHANES) I, II, III, and 1999–2002. Estimates were from multiple regression models with all surveys combined (n = 37 530) and were adjusted for the covariates in Table 2 [amount (in g) of food], Table 4 (energy density), and Table 5 (BMI): P for trend across surveys < 0.0001.

 
Our results suggest that changes in food selections of women over the past 3 decades were somewhat worse than those of men. For example, the increase in total amount of foods and beverages from NHANES I to NHANES 1999–2002 was similar in men and women (14% increase); however, the corresponding increase in mean energy intake was 8% in men and 18% in women. This may reflect a greater increase in energy density of foods selected by women. In all surveys, the energy density of snacks reported by women was higher than for men. In the NHANES I and II, the energy density of breakfast and evening foods was lower in women than in men; however, in later surveys, the sex differences in energy density of breakfast and evening foods disappeared, because the slope of energy density was steeper in women. These results suggest a putative reason for the sex disparity in the rate of increase in adiposity. [The prevalence of obesity and the percentage increase in prevalence of obesity is slightly higher among women than among men (1, 2)].

The decline in the number of adult Americans who report breakfast over the span of the 4 surveys in our study is in accord with a previous report that used 1 d of dietary data from the Continuing Survey of Food Intakes by Individuals, 1965–1991 (40). The finding of a decline in the number of Americans who reported breakfast should be viewed with concern given that breakfast consumption has been reported as a characteristic of successful weight-loss maintainers in the National Weight Control Registry (41). Also, breakfast intake is generally believed to be a positive predictor of adequacy of micronutrient intake, although the results vary with foods selected (42, 43).

In our study, the percentage of men (not women) mentioning a snack decreased from 91% in the NHANES I to 86% in the NHANES 1999–2002. Other reports on trends in snacking patterns were limited to children (17, 44) and young adults (18) and are not directly comparable to our study. Nicklas et al (44) reported that the number of eating and snacking episodes reported in a 24-h recall by children in the Bogalusa Heart Study declined from 1973 to 1994. In 2 reports from the Continuing Survey of Food Intakes by Individuals (1977–1996), the investigators concluded that the prevalence of snacking had increased among children aged 2–18 y and young adults aged 19–29 y (17, 18). Those studies estimated prevalence of snacking in a different reference period based on 3 d of dietary data that included a mixture of recalls and records and used a slightly different definition of snacking, and the prevalence rates were not adjusted for differences (if any) in characteristics of respondents in these surveys.

We urge cautious interpretation of our results because of changes in the methods used to collect the 24-h dietary recall in the NHANES over the course of the 4 surveys (19–23). Because the NCHS did not conduct any bridging studies to determine the systematic effect of changes in dietary methods on reporting of meals, snacks, or food and nutrient intakes, the confounding of time effect with the method effect remains a possibility. The multiple pass methods used for obtaining dietary recalls in later surveys may be expected to improve the recall of all possible eating and snacking episodes. However, the eating episodes in earlier surveys may be underreported; in which case, we may expect a positive secular trend in estimates of reporting of eating episodes (or other variables obtained from the dietary recall). As is evident from Tables 2 and 3, this was not the case. Notably, the observed shifts in these food consumption variables were relatively minor and rarely in the expected direction. For example, the mention of breakfast on the recall day declined consistently in both men and women, and the number of snacking episodes either declined (men) or remained unchanged (women) from 1971 to 2002. Nevertheless, the increase in reported quantity of foods, energy intake, and energy density in the NHANES III coincides with changes in dietary methods and is in the expected direction with improved recalls from the use of multiple-pass methods (45). Therefore, the results for these variables should be interpreted with due consideration for possibility of confounding. Clearly, the importance of bridging studies to allow understanding of these effects cannot be overstressed.

We also note that the recalls obtained in the NHANES I and II were limited to weekdays, whereas weekend days were included in later surveys (19–23). Because food consumption and selection behaviors on weekends may differ from weekdays, we included day of the recall as a covariate in regression models used to obtain the estimates presented in Tables 2–4. As mentioned in Subjects and Methods, the eating occasions we considered as breakfast or snack were labeled differently in the NHANES I and II than in later surveys. The extent to which our results reflect these differences is not known. Finally, the survey nutrient database used for estimating energy and nutrient intake has changed over the period of the 4 surveys (46). The database on nutrient composition of foods has expanded, and values of some nutrients may have changed because of improved analytic technology and food-sampling methods (46). However, energy content of foods (variable used in this study) is not among the attributes that have changed in the database.

Low-energy reporting has been noted in the NHANES II and the NHANES III and is more likely to occur in association with higher body weight and a low level of education (29–32). Low-energy reporting may attenuate the possible association of dietary variables and outcomes such as body weight examined in this study. In our evaluation of the association of food consumption patterns with obesity, we also examined these associations after adjustment for energy reporting status. The number of eating episodes, breakfast reporting, snacking, and, not surprisingly, the amount (in g) of food and its energy density predicted higher energy intake in all surveys. However, after adjustment for low-energy reporting status, only the amount (in g) of foods and beverages and the energy density of foods and nutritive beverages consistently predicted a higher BMI in both sexes.

In conclusion, our results do not support large increases in eating frequency, snacking, or evening eating by the American population over the past 3 decades. The quantity of foods and their energy density increased beginning with the NHANES III and may be implicated in contributing to higher energy intake and weight gain. However, these results coincide with changes in dietary methods in NHANES III and warrant cautious interpretation.


ACKNOWLEDGMENTS  
We thank Lisa Licitra Kahle for expert assistance with SAS and SUDAAN programming.

AKK was responsible for all aspects of this work: conceptualization of the study question, study design, operationalization of exposures and outcomes, data analysis, data interpretation, and preparation of the manuscript. BIG provided input on study design, developed methods for combining data from 4 national surveys, developed the analytic strategy, interpreted the data, and prepared the manuscript. Neither of the authors had a conflict of interest.


REFERENCES  

  1. Flegal KM, Carroll MD, Ogden CL, Johnson CL. Prevalence and trends in obesity among US adults, 1999–2000. JAMA2002; 288 :1723 –7.
  2. Hedley AA, Ogden CL, Johnson CL, Carroll MD, Curtin LR, Flegal KM. Prevalence of overweight and obesity among US children, adolescents, and adults, 1999–2002. JAMA2004; 291 :2847 –50.
  3. Economic Research Service, US Department of Agriculture. America's eating habits: changes and consequences. Washington, DC: USDA/Economic Research Service,1999 .
  4. Wright JD, Kennedy-Stephenson J, Wang CY, McDowell MA, Johnson CL. Trends in intake of energy and macronutrients–United States, 1971–2000. MMWR Morb Mortal Wkly Rep2004; 53 :80 –2.
  5. McCrory MA, Suen VMM, Roberts SB. Biobehavioral influences on energy intake and adult weight gain. J Nutr2002; 132 (suppl):3830 –4S.
  6. Kant AK, Graubard BI. Eating out in America, 1987–2000: trends and nutritional correlates. Prev Med2004; 38 :243 –9.
  7. Guthrie JF, Lin BH, Frazao E. Role of food prepared away from home in the American diet, 1977–78 versus 1994–96: changes and consequences. J Nutr Educ Behav2002; 34 :140 –50.
  8. Young LR, Nestle M. The contribution of expanding portion sizes to the US obesity epidemic. Am J Public Health2002; 92 :246 –9.
  9. Nielsen SJ, Popkin BM. Patterns and trends in food portion sizes, 1977–1998. JAMA2003; 289 :450 –3.
  10. Smicklas-Wright H, Mitchell DC, Mickle SJ, Goldman JD. Foods commonly eaten in the United States, 1989–1991 and 1994–1996: are portion sizes changing? J Am Diet Assoc2003; 103 :41 –7.
  11. Ello-Martin JA, Ledikwe JH, Rolls BJ. The influence of food portion size and energy density on energy intake: implications for weight management. Am J Clin Nutr2005; 82 (suppl):236 –41S.
  12. Kant AK, Ballard-Barbash R, Schatzkin A. Evening eating and its relation to self-reported body weight and nutrient intake in women, CSFII 1985–86. J Am Coll Nutr1995; 14 :358 –63.
  13. Kant AK, Schatzkin A, Ballard-Barbash R. Evening eating and subsequent long-term weight change in a national cohort. Int J Obes Relat Metab Disord1997; 21 :407 –12.
  14. De Castro JM. The time of day of food intake influences overall intake in humans. J Nutr2003; 58 :1071 –8.
  15. Kant AK, Schatzkin A, Graubard BI, Ballard-Barbash R. Frequency of eating occasions and weight change in the NHANES I Epidemiologic Follow-up Study. Int J Obes Relat Metab Disord1995; 19 :468 –74.
  16. Bellisle F, McDevitt R, Prentice AM. Meal frequency and energy balance. Br J Nutr1997; 77 (suppl):537 –48S.
  17. Jahns L, Siega-Riz AM, Popkin BM. The increasing prevalence of snacking among US children from 1977 to 1996. J Pediatr2001; 138 :493 –8.
  18. Zizza C, Siega-Riz AM, Popkin BM. Significant increase in young adults' snacking between 1977–1978 and 1994–1996 represents a cause for concern. Prev Med2001; 32 :303 –10.
  19. Cox DN, Mela DJ. Determination of energy density of freely selected diets: methodological issues and implications. Int J Obes Relat Metab Disord2000; 24 :49 –54.
  20. Kant AK, Graubard BI. Energy density of diets self-reported by American adults: association with food group intake, nutrient intake and body weight. Int J Obes Relat Metab Disord2005; 29 :950 –6.
  21. Ledikwe JH, Blanck HM, Khan LK, et al. Dietary energy density determined by eight calculation methods in a nationally representative United States population. J Nutr2005; 135 :273 –8.
  22. Rolls BJ, Bell EA, Thorwart ML. Water incorporated into a food but not served with a food decreases energy intake in lean women. Am J Clin Nutr1999; 70 :448 –55.
  23. Graubard BI, Korn EL. Predictive margins with survey data. Biometrics1999; 55 :652 –9.
  24. MacDiarmid J, Blundell J, Assessing dietary intake: who, what, and why of under-reporting. Nutr Res Rev1998; 11 :231 –53.
  25. Klesges RC, Eck LH, Ray JW. Who underreports dietary intake in a dietary recall? Evidence from the second National Health and Nutrition Examination Survey. J Consult Clin Psychol1995; 63 :438 –44.
  26. Briefel RR, Sempos CT, McDowell MA, et al. Dietary methods research in the third National Health and Nutrition Examination Survey: underreporting of energy intake. Am J Clin Nutr1997; 65 (suppl):203 –9S.
  27. Kant AK. Nature of dietary reporting by adults in the third National Health and Nutrition Examination survey, 1988–1994. J Am Coll Nutr2002; 21 :315 –27.
  28. McCrory MA, Jajduk CL, Roberts SB. Procedures for screening out inaccurate reports of dietary energy intake. Public Health Nutr2002; 5 :873 –82.
  29. Black AE, Prentice AM, Goldberg GR, et al. Measurement of energy expenditure provides insights into the validity of dietary measurements of energy intake. J Am Diet Assoc1993; 93 :572 –9.
  30. Korn EL, Graubard BI. Analysis of health surveys. New York, NY: Wiley, Inc,1999 :278 –303.
  31. SUDAAN, Release 9.0. Research Triangle Park, NC: Research Triangle Institute,2005 .
  32. Rolls BJ, Morris EL, Roe LS. Portion size of food affects energy intake in normal-weight and overweight men and women. Am J Clin Nutr2002; 76 :1207 –13.
  33. Rolls BJ, Roe LS, Meengs JS. Reductions in portion size and energy density of foods are additive and lead to sustained decreases in energy intake. Am J Clin Nutr2006; 83 :11 –7.
  34. Haines PS, Guilkey DK, Popkin BM. Trends in breakfast consumption between 1965 and 1991. J Am Diet Assoc1996; 96 :464 –70.
  35. Wyatt HR, Grunwald GK, Mosca CL, Klem ML, Wing RR, Hill JO. Long-term weight loss and breakfast in subjects in the National Weight Control Registry. Obes Res2002; 10 :78 –82.
  36. Ruxton CH, Kirk TR. Breakfast: a review of associations with measures of dietary intake, physiology and biochemistry. Br J Nutr1997; 78 :199 –213.
  37. Cho S, Dietrich M, Brown CJ, Clark CA, Block G. The effect of breakfast type on total daily energy intake and body mass index: results from the Third National Health and Nutrition Examination Survey (NHANES III). J Am Coll Nutr2003; 22 :296 –302.
  38. Nicklas TA, Morales M, Linares A, et al. Children's meal patterns have changed over a 21 year period. J Am Diet Assoc2004; 104 :753 –61.
  39. Conway JM, Ingwersen LA, Vinyard BT, Moshfegh AJ. Effectiveness of the US Department of Agriculture 5-step multiple-pass method in assessing food intake in obese and nonobese women. Am J Clin Nutr2003; 77 :1171 –8.
  40. Anderson E, Perloff B, Ahuja JKC, Raper N. Tracking nutrient changes for trends analysis in the United States. J Food Comp Anal2001; 14 :287 –94.
Received for publication March 10, 2006. Accepted for publication July 5, 2006.


作者: Ashima K Kant
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