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Adult Weight Management

AWM: Eating Frequency and Patterns (2013)

Citation:

Striegel-Moore RH, Franko DL, Thompson D, Affenito S, Kraemer HC. Night eating:  Prevalence and demographic correlates. Obesity (Silver Spring). 2006 Jan; 14 (1): 139-147.

PubMed ID: 16493132
 
Study Design:
Cross-Sectional Study
Class:
D - Click here for explanation of classification scheme.
Quality Rating:
Neutral NEUTRAL: See Quality Criteria Checklist below.
Research Purpose:

To examine the prevalence and correlates of night eating, the core behavioral symptom of night eating syndrome (NES) among adolescents and adults, using two public access survey databases of nationally representative samples.

Inclusion Criteria:

Data from two surveys:

  • The National Health and Nutrition Examination Survey (NHANES-III)
  • The Continuing Survey of Food Intakes by Individuals (CSFII) 1994 to 1996/1998.

For both surveys, a subpopulation of respondents who were age 13 years of older and either Hispanic or non-Hispanic black or white. Only data from the first day of the CSFII study were used to make it compatible with the NHANES III data.

Exclusion Criteria:

Younger children were not included because it was assumed that their eating times would be determined by their parents.

Description of Study Protocol:

Recruitment

Two large public access databases (NHANES-III and the CSFII) were used. Each contains detailed data from a representative sample of non-institutionalized, civilian U.S. residents concerning food intake, including all foods and liquids consumed over a 24-hour period, time of day of intake and type of meal.

Design

Cross-Sectional Study 

Blinding used

Not used 

Intervention

Not applicable 

Statistical Analysis

  • The percentage of individuals who exhibited night eating was estimated for each definition by season of the year, type of day (weekend vs. weekday), age group, gender and race/ethnicity
  • Due to the complex survey designs of CSFII and NHANES-III, weighting, stratification and clustering were taken into account in all statistical analyses 
  • Separate models were constructed for each survey and for each definition of night eating
  • Night eating by a given definition (1=yes; 0=no) served as the outcome variable
  • Prior to analysis, all covariates were centered as recommended
  • To adjust for the large number of statistical tests, a conservative level of statistical significance was adopted (P<0.01)
  • To examine the associated with obesity, obesity (binary) and BMI (continuous) were modeled as a function of night eating, controlling for age group, racial/ethnic group, gender and total calorie intake throughout the day
  • Obesity was modeled using logistic regression.
Data Collection Summary:

Timing of Measurements

  • NHANES-III was 1988 to 1994
  • CSFII was 1994 to 1996/1998. 

Dependent Variables

  • Night eating as defined as:
    • Consuming 25%+ of the total daily calories after 7 PM
    • Consuming 50%+ of the total daily calories after 7 PM 
    • Consuming anything after 11 PM regardless of the amount of calories consumed.

Independent Variables

  • Season of the year
  • Type of day (weekend vs. weekday)
  • Obesity.

Control Variables

  • Gender
  • Racial/ethnic group
  • Age group. 
Description of Actual Data Sample:
  • Initial N
    • NHANES-III was 33,994
    • CSFII was 21,662
  • Attrition (final N):
    • NHANES-III was 18,407
    • CSFII was 10,741
  • Age:
  NHANES-III CSFII
Adolescents 8.9% 9.1%
Young adults 24.6% 22.5%
Adults 51.5% 53.2%
Elderly 14.9% 15.2%
  • Ethnicity
  NHANES-III CSFII
Non-Hispanic white 78% 78%
Non-Hispanic black 11.8% 12.2%
Hispanic 10.2% 9.8%
  • Other relevant demographics
  NHANESIII CSFII
Men 47.5% 48.2%
Women 52.5% 51.8%
  • Anthropometrics: Not provided
  • Location: United States.

 

Summary of Results:

Key Findings

Demographic Characteristics

  • Estimates of demographic characteristics based on the two surveys were slightly different because they covered different timeframes
  • The largest racial/ethic group was non-Hispanic white and the largest age group was adults age 31 to 64 years.

Rates of Night Eating for Each Definition

  NHANES-III CSFII
Definition of Night Eating Percentage (95% CI) Percentage (95% CI)
25%+ kcal after 7PM 35.8 (34.3 to 37.2) 31.3 (29.9 to 32.8)
50%+ kcal after 7PM 12.5 (11.5 to 13.4) 10.9 (10 to 11.7)
Any eating after 11PM 12.2 (11.1 to 13.3) 9.3 (8.3 to 10.4)
  • Night eating by the first definition (25%+ kcal after 7 PM) was estimated to be present in more than one-third of the population
  • Night eating by the other two definitions (50%+ kcal after 7 PM and any eating after 11 PM) was less common; the estimates indicated that fewer than 13% met these definitions of night eating, regardless of survey
  • For all definitions of night eating, estimated rates were lower in CSFII than in NHANES-III.

Correlates of Night Eating

Weekdays vs. Weekend Days

  • Compared with CSFII, the food diaries in NHANES-III more often described eating on weekend days (36.1% of food diaries in NHANES-III vs. 30.7% in CSFII), possibly resulting in the aforementioned greater rates of night eating in NHANES-III
  • In both surveys, there was a main effect of type of day for the definitions involving consuming 25%+ and 50%+ of the daily calories after 7 PM  [Wald x2(1)=6.76 to 20.29, P<0.01), consistent with the results after adjusting for type of day, season, gender, age group, race/ethnicity and all possible two-way interactions among gender, age and race/ethnicity
  • Night eating was 1.2 to 1.4 times more likely to occur on weekends, depending on the definition and survey. Type of day was not associated with eating after 11 PM in either survey (P>0.05). Season effects were not significant for any definition or survey (P>0.05).

Demographic Characteristics

  • The main effects of gender and race/ethnicity differed across surveys
  • No main effects of gender and race/ethnicity were significant in CSFII (P>0.03)
  • In contrast, in NHANES-III, men were 1.2 to 1.4 times more likely than women to exhibit night eating for the definitions involving consuming 25%+ of the daily calories after 7 PM and any eating after 11 PM, respectively [Wald x2(1)=10.61/13.25, P<0.002)
  • Furthermore, in NHANES-III, by all definitions of night eating, black respondents were 1.3 to 1.6 times more likely than respondents in the other racial/ethnic groups to exhibit night eating by all definitions [Wald x2(1)=11.1 to 35.51, P<0.0009)
  • In both surveys, young adults were 1.2 to 1.6 times more likely than respondents in the other age groups to exhibit night eating by the definitions involving consuming 25%+ of the daily calories after 7 PM and any eating after 11 PM, respectively [Wald x2(1)=8.51 to 16.78, P<0.004)
  • In NHANES-III, Hispanic and black elderly individuals exhibited especially large decreases in the probability of eating after 11 PM compared with the other age groups, as exhibited by significant elderly-by-black and elderly-by-Hispanic interactions [Wald x2(1)=9.65/21.38, P<0.0001)
  • There were no main effects of season nor were there any significant interactions in either survey.

Night Eating and BMI/Obesity

  • In only one case, for the definition involving consuming 25%+ of the daily calories after 7 PM in NHANES-III was night eating associated with BMI [t(49)=-3.35, P=0.002), but the association was weak and in the direction opposite to that hypothesized: Predicted BMI for night eaters was -0.44 less than that for non-night eaters.
  • BMI was not associated with night eating by any other definition in either survey (P>0.02)
  • Similar models predicting the log odds of obesity revealed no association with night eating by any definition, regardless of survey (P>0.06). 

 

Author Conclusion:

This study used three definitions commonly found in the literature on NES to explore demographic correlates of this behavior and its possible relation with BMI or obesity. This study represents the first attempt to examine the prevalence and demographic correlates and association with BMI or obesity of night eating in a representative sample of U.S. adolescents and adults

Three main findings were found among the two surveys. One, as expected, the most inclusive definition (consuming 25% or after 7 PM) produced the highest prevalence. Two, for the first two definitions (which differed by the amount of calories consumed after 7 PM, namely 25% vs. 50%), but not the third definition (which involved eating very late during the night), day of the week mattered. And three, prevalence estimates varied considerably by age group, with adolescents being most likely and elderly individuals least likely to meet the criteria for night eating. In NHANES-III, but not CSFII, race/ethnicity moderated the relationship between age and night eating, with Hispanic and black elderly individuals being especially unlikely to meet criteria compared with the other age groups. Finally, gender and face/ethnicity effects were observed only in NHANES-III but not in CSFII; men were more likely than women and black Americans more likely than other racial/ethnic groups to meet the criteria for night eating.

The data from this study shows that eating 25% or more of one's daily calorie intake after 7 PM is common. In cultures where eating the evening meal occurs later in the day than in the U.S., the prevalence of night eating by this criterion would be far greater still. One approach to making the definition more applicable across different cultures is to use a time of day that is so late that in most cultures, it can be reasonably expected to be statistically abnormal to still be eating. Another strategy that has been employed is to define night eating more than a certain portion of one's daily intake after the evening meal, but this approach has its own disadvantage that the meaning of evening meal may not be the same for different people and that some may eat a considerable amount of food over a period of time in the late evening or at night rather then consuming an evening meal.

As expected, eating a considerable proportion of one's daily intake after 7 PM was more commonly reported on weekends, rather than during weekdays, likely reflecting culturally normative practices of cooking more elaborate dinners for family or friends or going out to eat on the weekend and this may mean eating later or eating more than usual. On the other hand, eating after 11 PM was not found to be associated with day of the week, suggesting that cultural practices play less of a role in eating very late in the evening. The results regarding age effects extend earlier work with a sample of adolescents, where it was found that with increasing age, night eating became increasing more common. In this study, night eating was most common among young adults and least common among the elderly.

Different prevalence estimates by gender or ethnic group were found in only NHANES-III and therefore need to be interpreted cautiously. These differences may reflect different subcultural practices, such as employment patterns, or different social norms about eating. Effects of both race/ethnicity and gender warrant further investigation. 

Unexpectedly, a significant inverse association between night eating and BMI for the definition of eating 25% or more after 7 PM was found. Individuals who reported night eating by this definition were slightly thinner than those who did not meet this night eating criterion. The analysis was adjusted for total calorie intake; hence, the difference is not due to night eaters consuming fewer calories in general. However, this effect was very small and was found in only one of the two surveys. This adds to other evidence from other studies that night eaters are less likely than others to be obese.

In conclusion, these findings suggest that researchers need to consider day of the week, age and possibly gender and race/ethnicity when examining population differences in night eating. Studies are needed to identify critical thresholds which may vary by culture for determining clinical significance of night eating.  This cross-sectional data did not support a link between the behavior of night eating and obesity in community samples. Future studies need to explore whether adding a frequency criterion or other behavior or affective components to identify a syndrome of NES will result in a significant association with obesity and if so will identify the mechanisms that mediate this association.

 

Funding Source:
Government: National Heart, Lung, and Blood Institute
Reviewer Comments:

The authors note the following limitations:

  • Because neither survey collected food diaries for consecutive days, night eating was defined using single day records. Hence, it was not possible to use a more restrictive definition of night eating, requiring the behavior to occur on a recurrent basis. It cannot be ruled out that a more regular pattern of night eating might be associated with elevated BMI or obesity.
  • Also, the two surveys differ in several respects, suggesting that greater confidence should be placed in the results that were consistent across surveys
  • The survey data did not permit examining specifically whether participants experienced nocturnal eating episodes involving awakening during the night and eating before returning to sleep, nor did they include information about the participants' sleeping patterns or sleep disorder symptoms
  • The data was cross-sectional and prospective studies are needed to further determine the clinical significance of night eating
  • Information about education and employment status is needed to better account for different prevalences.
Quality Criteria Checklist: Primary Research
Relevance Questions
  1. Would implementing the studied intervention or procedure (if found successful) result in improved outcomes for the patients/clients/population group? (Not Applicable for some epidemiological studies) Yes
  2. Did the authors study an outcome (dependent variable) or topic that the patients/clients/population group would care about? Yes
  3. Is the focus of the intervention or procedure (independent variable) or topic of study a common issue of concern to dieteticspractice? Yes
  4. Is the intervention or procedure feasible? (NA for some epidemiological studies) Yes
 
Validity Questions
1. Was the research question clearly stated? Yes
  1.1. Was (were) the specific intervention(s) or procedure(s) [independent variable(s)] identified? Yes
  1.2. Was (were) the outcome(s) [dependent variable(s)] clearly indicated? Yes
  1.3. Were the target population and setting specified? Yes
2. Was the selection of study subjects/patients free from bias? Yes
  2.1. Were inclusion/exclusion criteria specified (e.g., risk, point in disease progression, diagnostic or prognosis criteria), and with sufficient detail and without omitting criteria critical to the study? Yes
  2.2. Were criteria applied equally to all study groups? Yes
  2.3. Were health, demographics, and other characteristics of subjects described? Yes
  2.4. Were the subjects/patients a representative sample of the relevant population? Yes
3. Were study groups comparable? Yes
  3.1. Was the method of assigning subjects/patients to groups described and unbiased? (Method of randomization identified if RCT) Yes
  3.2. Were distribution of disease status, prognostic factors, and other factors (e.g., demographics) similar across study groups at baseline? Yes
  3.3. Were concurrent controls or comparisons used? (Concurrent preferred over historical control or comparison groups.) Yes
  3.4. If cohort study or cross-sectional study, were groups comparable on important confounding factors and/or were preexisting differences accounted for by using appropriate adjustments in statistical analysis? Yes
  3.5. If case control study, were potential confounding factors comparable for cases and controls? (If case series or trial with subjects serving as own control, this criterion is not applicable.) Yes
  3.6. If diagnostic test, was there an independent blind comparison with an appropriate reference standard (e.g., "gold standard")? N/A
4. Was method of handling withdrawals described? Yes
  4.1. Were follow-up methods described and the same for all groups? Yes
  4.2. Was the number, characteristics of withdrawals (i.e., dropouts, lost to follow up, attrition rate) and/or response rate (cross-sectional studies) described for each group? (Follow up goal for a strong study is 80%.) Yes
  4.3. Were all enrolled subjects/patients (in the original sample) accounted for? Yes
  4.4. Were reasons for withdrawals similar across groups? Yes
  4.5. If diagnostic test, was decision to perform reference test not dependent on results of test under study? N/A
5. Was blinding used to prevent introduction of bias? No
  5.1. In intervention study, were subjects, clinicians/practitioners, and investigators blinded to treatment group, as appropriate? N/A
  5.2. Were data collectors blinded for outcomes assessment? (If outcome is measured using an objective test, such as a lab value, this criterion is assumed to be met.) No
  5.3. In cohort study or cross-sectional study, were measurements of outcomes and risk factors blinded? No
  5.4. In case control study, was case definition explicit and case ascertainment not influenced by exposure status? N/A
  5.5. In diagnostic study, were test results blinded to patient history and other test results? N/A
6. Were intervention/therapeutic regimens/exposure factor or procedure and any comparison(s) described in detail? Were interveningfactors described? No
  6.1. In RCT or other intervention trial, were protocols described for all regimens studied? N/A
  6.2. In observational study, were interventions, study settings, and clinicians/provider described? N/A
  6.3. Was the intensity and duration of the intervention or exposure factor sufficient to produce a meaningful effect? No
  6.4. Was the amount of exposure and, if relevant, subject/patient compliance measured? N/A
  6.5. Were co-interventions (e.g., ancillary treatments, other therapies) described? N/A
  6.6. Were extra or unplanned treatments described? N/A
  6.7. Was the information for 6.4, 6.5, and 6.6 assessed the same way for all groups? Yes
  6.8. In diagnostic study, were details of test administration and replication sufficient? N/A
7. Were outcomes clearly defined and the measurements valid and reliable? No
  7.1. Were primary and secondary endpoints described and relevant to the question? ???
  7.2. Were nutrition measures appropriate to question and outcomes of concern? Yes
  7.3. Was the period of follow-up long enough for important outcome(s) to occur? N/A
  7.4. Were the observations and measurements based on standard, valid, and reliable data collection instruments/tests/procedures? Yes
  7.5. Was the measurement of effect at an appropriate level of precision? Yes
  7.6. Were other factors accounted for (measured) that could affect outcomes? No
  7.7. Were the measurements conducted consistently across groups? Yes
8. Was the statistical analysis appropriate for the study design and type of outcome indicators? Yes
  8.1. Were statistical analyses adequately described and the results reported appropriately? Yes
  8.2. Were correct statistical tests used and assumptions of test not violated? Yes
  8.3. Were statistics reported with levels of significance and/or confidence intervals? Yes
  8.4. Was "intent to treat" analysis of outcomes done (and as appropriate, was there an analysis of outcomes for those maximally exposed or a dose-response analysis)? N/A
  8.5. Were adequate adjustments made for effects of confounding factors that might have affected the outcomes (e.g., multivariate analyses)? Yes
  8.6. Was clinical significance as well as statistical significance reported? Yes
  8.7. If negative findings, was a power calculation reported to address type 2 error? N/A
9. Are conclusions supported by results with biases and limitations taken into consideration? Yes
  9.1. Is there a discussion of findings? Yes
  9.2. Are biases and study limitations identified and discussed? Yes
10. Is bias due to study's funding or sponsorship unlikely? Yes
  10.1. Were sources of funding and investigators' affiliations described? Yes
  10.2. Was the study free from apparent conflict of interest? Yes