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Abstract

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods and Procedures
  5. Results
  6. Discussion
  7. Acknowledgment
  8. Disclosure
  9. REFERENCES

This study examined cross-sectional and 5-year longitudinal associations between the frequency of family meals and overweight status (>85th percentile for age and gender) in a large, diverse population of adolescents (n = 2,516). The population included two cohorts (midadolescence to young adulthood, n = 1,710, and early adolescence to midadolescence, n = 806). Logistic regression models tested cross-sectional and longitudinal (1999–2004) associations between family meal frequency and overweight status. Two sets of models are presented: (i) models adjusted only for baseline demographic characteristics and (ii) models also adjusted for physical activity, sedentary behaviors, and energy intake. Longitudinal models adjusted for baseline overweight status. Although significant inverse associations between family meal frequency and overweight status were observed for early adolescent females in all cross-sectional models (P < 0.001), longitudinal associations were not significant. Neither cross-sectional nor longitudinal associations were significant for males of either cohort and older females in any models. Young adolescent females who do not eat meals with their families may be at risk for overweight; however, the increased risk may not persist over a 5-year period. Eating family meals during high school may not protect against overweight during young adulthood. Although previous longitudinal research has suggested significant dietary and psychosocial benefits related to family meal frequency, the weight-related benefits of family meals may be more complex and deserving of further study, including an examination of the quality and quantity of food consumed at family meals.


Introduction

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods and Procedures
  5. Results
  6. Discussion
  7. Acknowledgment
  8. Disclosure
  9. REFERENCES

More than 30% of children and youth aged 9–19 years are overweight or obese, and rates continue to increase (1). Parents play a critical role in the development of children's eating habits and weight-related behaviors through exposure, availability, and accessibility of foods in the home (2). The family meal setting has the potential to substantially impact the dietary intake of children (3) and may provide an important avenue for obesity prevention. However, opportunities for families to have meals together have been negatively affected by changes in our society (4,5), and data suggest that the frequency of family meals may be declining (5).

Positive associations between nutrient intake patterns, including intakes of fiber, fat, several vitamins and minerals, and fruits and vegetables, and family meal frequency have been previously reported among children (6) and adolescents (7,8,9). Similarly, the frequency of family meals has also been shown to have significant inverse associations with consumption of soft drinks (6,9) and high-fat foods (6). Research has also found significant inverse associations with disordered eating (10,11,12,13,14). Thus, there is evidence that family meal frequency may promote nutritious dietary intake and protect against disordered eating. Only a handful of studies have examined the associations of family meal frequency and overweight or obesity. Gillman et al.(6) found a modest inverse association between age-adjusted BMI and family dinner frequency among youth aged 9–14 years in a cross-sectional study. Taveras et al. (14) reanalyzed these data controlling for potential covariates (socioeconomic status (SES), age, maturational stage, baseline height, race/ethnicity, girls' menstrual status, physical activity, inactivity, and energy intake) and found that the odds of being overweight were significantly lower among youth who reported eating family dinner most or every day in a typical week during the past year. In addition, Taveras et al. (14) also assessed longitudinal associations between family dinner frequency and the 1-year incidence of becoming overweight; however, the significant cross-sectional associations did not hold up in the longitudinal analyses. In an analysis of a nationally representative, racially diverse population of adolescents, Sen (15) examined racial/ethnic differences in the associations between family dinner frequency and overweight status, incidence of overweight, and cessation of overweight over a 3-year period among adolescents (adjusting for age, puberty, height, and several other demographic characteristics) and found that family dinner frequency was inversely associated with being overweight among white adolescents in both cross-sectional and longitudinal analyses; however, findings were not significant for Black and Hispanic youth. Similar results were found in longitudinal analyses for the cessation of overweight. Most recently, Gable et al. (16) assessed family meal frequency and overweight onset in a longitudinal study of school-age children while controlling for gender, race, and SES, and found significant inverse associations between family meal frequency and overweight onset.

The primary purpose of the present investigation is to describe associations between the frequency of family meals and overweight status over a 5-year period in a large and ethnically diverse population of adolescent males and females. With the exception of the study of early school-age children (16), previous research has been limited in time to a 1-year incidence of overweight. Thus, this study will extend previous research by assessing 5-year associations between family meal frequency and overweight. This study will also elucidate the influence that potential confounding variables (e.g., physical activity, energy intake) have on the associations between family meal frequency and overweight by presenting findings with adjustment of demographic characteristics only and then with additional adjustments of activity level and energy intake. All of the studies examining family meal frequency and overweight to date have adjusted for demographic factors (or stratified by them); only the study by Taveras et al. (14) further adjusted for activity and energy intake, and presented only adjusted findings. A deeper understanding of how statistical adjustments influence the associations between family meal frequency and overweight are warranted. This study will also present analyses stratified by cohort (high school students moving into young adulthood (C1) and students of early adolescence moving into high school (C2)) as the association between family meal frequency and overweight may be different as adolescents develop. Finally, this study will take advantage of the racial/ethnic diversity of the Project EAT sample and assess racial/ethnic differences in the associations between family meal frequency and overweight.

Methods and Procedures

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods and Procedures
  5. Results
  6. Discussion
  7. Acknowledgment
  8. Disclosure
  9. REFERENCES

Study design and participants

Project EAT-II is a follow-up study of Project EAT-I, a study of nutrition and weight status among adolescents. In 1998–1999, in Project EAT-I, 4m746 junior and senior high students from 31 Minnesota schools completed in-class surveys and had height and weight measured by trained research staff. Project EAT-II resurveyed participants by mail 5 years later (2003–2004). Of the original Project EAT-I study population, 1,074 (22.6%) were lost to follow-up (Project EAT-II) for various reasons, primarily missing contact information (n = 411) and no address found at follow-up (n = 591). Of the remaining 3,672 participants contacted by mail, 2,516 completed surveys, representing 53.0% of the original cohort and 68.4% of participants who could be contacted for Project EAT-II, and this is the sample whose data are analyzed in this study. Study procedures were approved by the University of Minnesota Human Subjects' committee.

Main measures

BMI was derived from the formula: weight in kilograms divided by the square of height in meters based on the students' self-reported height and weight data. Measured height and weight were available only at Time 1 (T1); self-reported data were collected at Time 2 (T2). Analyses of self-reported and measured height and weight among this sample at T1 indicated that values are highly correlated (r = 0.85 for adolescent females and 0.89 for adolescent males) (17). Thus, to be consistent across cross-sectional and longitudinal analyses, we chose to use self-reported height and weight data in this study. Adolescent BMI was adjusted using gender- and age-specific cutoff points (18). Adult overweight status was based on the Must et al. classification (19,20) (BMI >85th and 95th percentiles for gender and age) among the older cohort to avoid the discontinuity that occurs across the 20-year age boundary if the usual adult classification is used, by which, for both genders, overweight is defined as BMI >25 kg/m2 and obesity as BMI ≥30 kg/m2.

Frequency of family meals was assessed with the item, “During the past seven days, how many times did all, or most, of your family living in your house eat a meal together?” Response options were “Never,” “1–2 times,” “3–4 times,” “5–6 times,” “7 times,” and “More than 7 times.” For analyses, response option categories were collapsed as follows: “Never,” “1–2 times,” “3 or more times” to reflect no, infrequent, and frequent family meals, respectively.

Covariates

Physical activity was assessed with a modified version of the Leisure Time Exercise Questionnaire (21). Students were asked to report the number of hours they spent during the usual week in strenuous exercises (e.g., biking fast, running, swimming laps) and moderate exercises (e.g., baseball, easy bicycling). Response options consisted of 0, <0.5, 0.5 to 2, 2.5–4, 4.5–6, and >6 h/week. Responses were recoded to 0, 0.3, 1.3, 3.3, 5.3, and 8 h/week, and then total hours per week of vigorous physical activity and moderate physical activity were calculated as summative scores.

Sedentary behavior was measured by asking students the average number of hours they engaged in sedentary activities (watching television and videos, reading, doing homework, spending time on a computer) on weekdays and on weekends (22). Response options were 0, 0.5, 1, 2, 3, 4, and ≥5 h, and then an average number of hours was calculated separately for each behavior and then summed together. A total number of hours that combined weekday and weekend hours was used in the present study.

Energy intake was measured with the 149-item Youth/Adolescent Food Frequency Questionnaire. Total energy (kcals/day) from all foods was calculated as an overall measure of energy intake. The Youth/Adolescent Food Frequency Questionnaire has been shown to be valid and reliable for use with adolescents (23,24).

Demographic characteristics assessed included SES, race/ethnicity, age, gender, and cohort (C2: middle school moving to high school; C1: high school moving to young adulthood). SES was estimated by an algorithm that included education, employment, and poverty indicators, and resulted in five levels of SES (12). Students self-reported their race/ethnicity. Students were classified into either middle school (grades 7–8; 34%) or high school (grades 9–12; 66%) at baseline, corresponding to cohorts C2 and C1, respectively.

Statistical analysis

Logistic regression analyses (odds ratios and 95% confidence intervals) tested the cross-sectional baseline associations between family meal frequency and overweight, as well as associations between family meal frequency at T1 and overweight at T2 (stratified by cohort and gender). For analyses, model 1 assessed the relationships adjusted for baseline demographic characteristics (age, race/ethnicity, SES) only, and model 2 also adjusted for physical activity, sedentary behavior, and energy intake. All longitudinal analyses also adjusted for baseline overweight status in both models. Threshold for significance was set at P < 0.05. Attrition from T1 to T2 did not occur completely at random. Thus, in all analyses, the data were weighted to adjust for differential response rates using the response propensity method (25), resulting in estimates representative of a random sample of the original Project EAT-I sample. A full description of the propensity-weighting method can be found elsewhere (26). All analyses were conducted in SAS (SAS/STAT Release 8. 8.2; SAS Institute, Cary, NC).

Results

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods and Procedures
  5. Results
  6. Discussion
  7. Acknowledgment
  8. Disclosure
  9. REFERENCES

Participant characteristics and baseline behaviors

As shown in Table 1, approximately half of the sample described their race/ethnicity as white, followed in prevalence by Asian American, African American, Latino, mixed/other, and Native American. Students in the younger cohort were more ethnically diverse. SES was divided into approximate quintiles. At baseline, the average age of students was about 15 years. Three-quarters of the sample reported eating family meals at least three times per week. On average, hours spent per week being physically active was 9.5, with almost 42 h of sedentary behavior. Energy intake was about 2,000 kcal on average. Approximately 25% of students met criteria (>85% BMI) for overweight/obesity. These demographic characteristics are almost identical to the full Project EAT-I sample. At follow-up, time spent being physically active was ∼8 h, with >45 h of sedentary behavior; energy intake was ∼1,800 kcal/day; and >26% of students met criteria for overweight.

Table 1.  Description of the longitudinal sample by gender and cohort at time 1 and time 2a
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Cross-sectional associations between family meal frequency and overweight status

Table 2 shows odds ratios and 95% confidence intervals of baseline overweight status by baseline family meal frequency, stratified by cohort and gender, for models 1 and 2. Family meal frequency was not significantly associated with overweight status in males of either cohort, nor for older cohort females in either adjusted models in cross-sectional analyses. However, younger cohort females (C2) reporting no family meals in the past week at baseline were significantly more likely to be overweight at baseline than females who reported eating three or more meals per week with their family members in the model adjusted for demographic characteristics (Wald χ2 (3) = 7.8, P < 0.05), and the model that also adjusted for physical activity and energy intake (Wald χ2 (3) = 7.8, P < 0.05). Similar findings were found when the uppermost baseline family meal frequency category was divided into three to six meals per week and seven or more meals per week (data not shown).

Table 2.  Odds ratios (95% confidence intervals) of overweight status by family meal frequency (cross-sectional)
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Longitudinal associations between family meal frequency and overweight status

Overweight status at T2 by baseline family meal frequency was also examined (see Table 3), stratified by cohort and gender for models 1 and 2. Family meal frequency was not associated with overweight status in males or females of either cohort in any longitudinal models.

Table 3.  Odds ratios (95% confidence intervals) of overweight status by family meal frequency (longitudinal)
inline image

Associations between family meal frequency and overweight status by race/ethnicity

In addition, we assessed the cross-sectional and longitudinal associations between family meal frequency and overweight stratified by race/ethnicity (white, n = 1,525; African American, n = 274; Latino, n = 105; and Asian, n = 447). Owing to relatively small samples in the ethnic minority groups, we adjusted our analytic plan by stratifying by cohort and adjusting for gender, SES, and age (i.e., model 1 for larger sample); but we did not adjust for energy expenditure variables (i.e., model 2 for larger sample). In cross-sectional analyses, family meal frequency was associated with overweight status only among white youth in the younger cohort when analyses adjusted for gender, SES, and age (F(2) = 6.1, P < 0.05), with adolescents reporting never eating family meals at higher risk for overweight (odds ratio = 2.3, confidence interval = 1.0–5.5) than adolescents reporting three or more meals per week. Longitudinal associations between family meal frequency and overweight were not significant among white youth. Neither cross-sectional nor longitudinal associations between family meal frequency and overweight were significant among Black or Asian students of either cohort in any models. Among Latino adolescents, neither cross-sectional nor longitudinal associations between family meal frequency and overweight were significant among the older cohort, and models were not stable in the younger cohort.

Discussion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods and Procedures
  5. Results
  6. Discussion
  7. Acknowledgment
  8. Disclosure
  9. REFERENCES

The primary purpose of the present investigation was to examine associations between the frequency of family meals and overweight over a 5-year period in a large and diverse population of adolescent males and females and to further elucidate the influence of potential confounders in these associations. Although significant inverse associations between family meal frequency and overweight status were observed for early adolescent females in all cross-sectional models, longitudinal associations were not significant. Neither cross-sectional nor longitudinal associations were significant for males of either cohort and older females in any models.

Our findings of significant inverse associations between family meal frequency and overweight status solely among young adolescent females only in cross-sectional analyses corroborates previous research findings of adolescents (14,15). Previous research has shown that family meal frequency decreases with age (6,8). These findings indicate that it is normative for older adolescents to be spending less time with their families. Perhaps the younger females in the present study who did not report eating meals with their families are at risk for overweight because eating family meals is nutritionally beneficial (8), and they are at an age where it is normative to be spending mealtime with family. Moreover, the different findings for younger males and females may be explained by the fact that young females are particularly at risk for eating disturbances such as unhealthy weight-control behaviors and dieting. If young females do not have the opportunity to observe healthy eating behaviors at the family meal, they may be more likely to engage in dieting which have been shown to be associated with weight gain (27). Indeed, in a similar analysis examining longitudinal associations between family meal frequency and disordered eating among Project EAT participants, we found significant associations between the frequency of family meals and extreme weight-control behaviors in females, but not in males (28). Our null findings of a longitudinal association among adolescents, along with the significant longitudinal findings in the work by Gable et al. (16) among school-age children, suggest that interventions aimed at promoting healthful family meals to decrease excessive weight gain should target young, school-age children.

The adjustments we made to our analyses to ensure stable estimates of the associations between family meal frequency and overweight stratified by race/ethnicity highlight the need for very large, racially diverse samples for understanding these relationships. Sen (15) was able to examine differences across race/ethnicity in a sample of 5,014, but chose not to include gender in the model or stratify analyses by gender, perhaps to lend more power to the race analysis. We chose to adjust for gender in our analyses given differences found by gender in previous work, but were prohibited by sample size to stratify by gender. Further studies are needed to evaluate whether there are racial/ethnic differences in the relationship between family meal frequency and overweight, whether gender differences are apparent, and how potential confounders influence the relationships. Our study provides preliminary data in this effort. This work may be most important to do with samples of young children who eat more of their meals at home, given the longitudinal associations found between family meal frequency and overweight status in this age group (16).

In our interest to elucidate the influence of potential confounding variables, it is apparent that statistical adjustment of factors that reflect energy balance did not affect study findings. This suggests that when assessing associations between family meal frequency and overweight, careful examination of potential covariates should be conducted, and excluded if warranted, to highlight influential variables. Uncovering the important contributors to the relationship between family meals and overweight would assist with the development of effective intervention programs. In particular, more details about the context of the meals (who exactly shares the meals with the adolescent) and the nutritional quality of meals would benefit future intervention programming.

This study has limitations that deserve mention. Although objective measures of height and weight were collected at baseline, only self-reported height and weight were available at follow-up; thus, we made the decision to be consistent and to use overweight calculations based on self-reported height and weight for both cross-sectional and longitudinal analyses. High correlations between measured and self-reported BMIs at time 1 lessen our concern about using the self-report measure (17).

Several strengths are also apparent in our study such as the large racially/ethnically diverse sample, and examination of two cohorts of youth; one moving from middle school to high school and the other moving from high school to young adulthood. In addition, this study extended previous research examining family meal frequency and overweight by examining these relationships over a 5-year period of time rather than a maximum of 3 years in research to date (15,16) while exploring the influences of potential confounding variables such as variables associated with energy balance.

Previous research utilizing the Project EAT dataset and other studies have demonstrated strong associations between more frequent family meals and improved dietary intake (6,7,8,9), better psychosocial well-being (10), and fewer disordered eating behaviors (10,11,12,13). Thus, it should follow that more frequent family meals would protect adolescents from excessive weight gain. However, associations with obesity are more complex given the multifactorial etiology of obesity and the diversity of types and quantities of foods eaten at family meals. Within interventions to increase family meal frequency, it may be important to address the quality of food served and the impact on weight status among family members.

Acknowledgment

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods and Procedures
  5. Results
  6. Discussion
  7. Acknowledgment
  8. Disclosure
  9. REFERENCES

This study was supported financially by Grant R40 MC 00319-02 from the Maternal and Child Health Bureau (Title V, Social Security Act), Health Resources and Service Administration, US Department of Health and Human Services and from the General Mills Bell Institute of Health and Nutrition.

REFERENCES

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods and Procedures
  5. Results
  6. Discussion
  7. Acknowledgment
  8. Disclosure
  9. REFERENCES
  • 1
    Ogden CL, Carroll MD, Curtin LR, McDowell MA, Tabak CJ, Flegal KM. Prevalence of overweight and obesity in the United States, 1999–2004. JAMA 2006; 295: 15491555.
  • 2
    Birch LL, Davison KK. Family environmental factors influencing the developing behavioral controls of food intake and childhood overweight. Pediatr Clin North Am 2001; 48: 893907.
  • 3
    Dietz WH, Gortmaker SL. Preventing obesity in children and adolescents. Annu Rev Public Health 2001; 22: 337353.
  • 4
    Perry C, Kelder S, Komro K. The social world of adolescents: family, peers, schools and the community. In: Millstein S, Peterson A, Nightengale E (eds). Promoting the Health of Adolescents: New Directions for the 21st Century. Oxford Univ. Press: New York, 1993, pp 7396.
  • 5
    Nicklas TA, Morales M, Linares A et al. Children's meal patterns have changed over a 21-year period: The Bogalusa Heart Study. J Am Diet Assoc 2004; 104: 753761.
  • 6
    Gillman MW, Rifas-Shiman SL, Frazier L et al. Family dinner and diet quality among older children and adolescents. Arch Fam Med 2000; 9: 235240.
  • 7
    Videon TM, Manning CK. Influences on adolescent eating patterns: the importance of family meals. J Adol Health 2003; 32: 365373.
  • 8
    Neumark-Sztainer D, Hannan PJ, Story M, Croll J, Perry CL. Family meal patterns: associations with sociodemographic characteristics and improved dietary intake among adolescents. J Am Diet Assoc 2003; 103: 317322.
  • 9
    Larson NI, Neumark-Sztainer D, Hannan PJ, Story M. Family meals during adolescence are associated with higher diet quality and healthful meal patterns during young adulthood. J Am Diet Assoc 2007; 107: 15021510.
  • 10
    Fulkerson JA, Story M, Mellin A, Leffert N, Neumark-Sztainer D, French SA. Family dinner meal frequency and adolescent development: Relationships with developmental assets and high-risk behaviors. J Adolesc Health 2006; 39: 337345.
  • 11
    Ackard DM, Neumark-Sztainer D. Family mealtime while growing up: associations with symptoms of bulimia nervosa. Eat Disord 2001; 9: 239249.
  • 12
    Fulkerson JA, Strauss J, Neumark-Sztainer D, Story M, Boutelle KN. Correlates of psychosocial well-being among overweight adolescents: the role of the family. J Consult Clin Psychol 2007; 75: 181186.
  • 13
    Neumark-Sztainer D, Eisenberg ME, Fulkerson JA, Story M, Larson NI. Do family meals protect adolescents from disordered eating behaviors? Arch Pediatr Adolesc Med 2008; 162: 1722.
  • 14
    Taveras EM, Rifas-Shiman SL, Berkey CS et al. Family dinner and adolescent overweight. Obes Res 2005; 13: 900906.
  • 15
    Sen B. Frequency of family dinner and adolescent body weight status: evidence from the National Longitudinal Survey of Youth, 1997. Obesity 2006; 14: 22662276.
  • 16
    Gable S, Chang Yiting, Krull JL. Television watching and frequency of family meals are predictive of overweight onset and persistence in a national sample of school-age children. J Am Diet Assoc 2007; 107: 5361.
  • 17
    Himes JH, Hannan P, Wall M, Neumark-Sztainer D. Factors associated with errors in self-reports of stature, weight, and body mass index in Minnesota adolescents. Ann Epidemiol 2005; 15: 272278.
  • 18
    Himes JH, Dietz WH. Guidelines for overweight in adolescent preventive services: recommendations from an expert committee. The Expert Committee on Clinical Guidelines for Overweight in Adolescent Preventive Services. Am J Clin Nutr 1994; 59: 307316.
  • 19
    Must A, Dallal GE, Dietz WH. Reference data for obesity: 85th and 95th percentiles of body mass index (wt/ht2) and tricep skinfold thickness. Am J Clin Nutr 1991; 53: 839846.
  • 20
    Must A, Dallal GE, Dietz WH. Reference data for obesity: 85th and 95th percentiles of body mass index (wt/ht2)-a correction. Am J Clin Nutr 1991; 54: 773.
  • 21
    Godin G, Shephard RJ. A simple method to assess exercise behavior in the community. Can J Appl Sport Sci 1985; 10: 141146.
  • 22
    Utter J, Neumark-Sztainer D, Jeffery R, Story M. Couch potatoes or French fries: are sedentary behaviors associated with body mass index, physical activity, and dietary behavior among adolescents? J Am Diet Assoc 2003; 103: 12981305.
  • 23
    Rockett HR, Breitenbach M, Frazier AL et al. Validation of a youth/adolescent food frequency questionnaire. Prev Med 1997; 26: 808816.
  • 24
    Rockett HR, Wolf AM, Colditz GA. Development and reproducibility of a food frequency questionnaire to assess diets of older children and adolescents. J Am Diet Assoc 1995; 95: 336340.
  • 25
    Little RJA. Survey nonresponse adjustments for estimates of means. Int Stat Rev 1986; 54: 139157.
  • 26
    Neumark-Sztainer D, Wall M, Eisenberg ME, Story M, Hannan PJ. Overweight status and weight control behaviors in adolescents: longitudinal and secular trends from 1999–2004. Prev Med 2006; 43: 5259.
  • 27
    Neumark-Sztainer D, Wall M, Haines J, Story M, Eisenberg ME. Why does dieting predict weight gain in adolescents? Findings from Project EAT-II: a 5-year longitudinal study. J Am Diet Assoc 2007; 107: 448455.
  • 28
    Neumark-Sztainer D, Eisenberg ME, Fulkerson JA, Story M, Larson NI. Do family meals protect adolescents from disordered eating behaviors? Arch Pediatr Adolesc Med 2008; 162: 1722.