Diet quality and feelings of worry, sadness or unhappiness in Canadian children.

McMartin, Seanna E. ; Willows, Noreen D. ; Colman, Ian 等

Mood disorders constitute an important public health concern because they are prevalent, affect quality of life, are an established risk factor for suicide, and are a source of substantive economic costs to society. (1) Diet quality is an established public health concern that contributes to excess body weight and consequent chronic diseases. (2-4) Although some research points to a link between nutrition and mental health, most of the extant literature has focused on adult populations. (5-8) Studies examining the relationship between diet quality and mental health in early adolescence found that children consuming lower quality diets were more likely to have poor mental health outcomes. (9-11) A prospective study from Nova Scotia found that greater variety in the diet was significantly associated with a lower rate of being diagnosed with internalizing disorder during the three years of follow-up. (10) A study among Australian adolescents found lower diet quality to be associated with poorer mental health outcomes both cross-sectionally and prospectively. (9) Regional dietary differences and distinct national regulations regarding food fortification policies limit generalizations related to the importance of diet for mental health. Broader evidence from more studies and local evidence will allow to better tailor public health initiatives to promote healthy eating and to improve mental health.

Studies have indicated that children suffering from depressive symptoms that do not meet diagnostic criteria have higher rates of depression and other mental health disorders in adulthood. (12,13) Therefore, feelings of worry, sadness or unhappiness may represent an early marker for poor mental well-being later in life. Given that other studies have identified the longitudinal relationships of diet and mental health, we sought to understand the importance of diet quality for early markers of mental well-being, specifically feelings of worry, sadness or unhappiness. This understanding is important to policy makers to develop strategies for early public health interventions.

METHODS

Sample

This study used data from the Raising healthy Eating and Active Living Kids in Alberta study (REAL Kids Alberta), a cross-sectional, province-wide survey examining diet quality, physical activity and wellness of grade 5 students (aged 10-11 years) across Alberta, Canada. The study, including data collection and parental informed consent forms, was approved by the Health Research Ethics Board of the University of Alberta. Details regarding the questionnaires used are available through the project's website: www.REALKidsAlberta.ca. The data collection procedures have been described in detail elsewhere. (14) In brief, surveys were administered in 2008 and in 2010. In 2008, 5,321 grade 5 students received a parent survey and parental consent form. Of these students, 3,704 received parental consent to participate, 3,421 of whom completed the surveys (64% participation rate). In 2010, 3,687 of 5,597 grade 5 students received parental consent to participate, 3,398 of whom completed the surveys (61% participation rate). In concordance with established recommendations for the analysis of food frequency data, we excluded subjects with calorie intakes of less than 500, and of more than 5,000 kilocalories per day, (15) leaving a total sample of 6,528 students.

Exposure of interest: Diet quality

Nutrient intake and dietary habits were examined using the Harvard Food Frequency Youth/Adolescent Questionnaire (YAQ). (16) This self-administered questionnaire is used to assess usual dietary intake over the previous twelve months. The YAQ is designed for children and youth aged 9 to 18 years, and has been validated among this age group. (16)

On the basis of students' responses to the YAQ and Canadian Nutrient Files, (17) we assessed nutrient intake, energy intake, and daily servings of vegetables and fruit. On the basis of these quantities, we calculated the Diet Quality Index-International (DQI-I), a commonly used index of diet quality that incorporates several dietary characteristics. (18,19) The DQI-I score ranges from 0 to 100, with higher scores indicating a higher diet quality. The DQI-I consists of four component scores: 1) variety, 2) adequacy, 3) moderation, and 4) balance. (18)

Outcome of interest: Feelings of worry, sadness or unhappiness

The EuroQoL for youth (EQ-5D-Y) is a modified version of the adult EQ-5D instrument that measures health-related quality of life. (20) The EQ-5D-Y is a widely used and validated instrument, and is translated in 25 languages. (20) Students are asked to describe the degree to which they are currently feeling "worried, sad or unhappy", with three response options: "you are not worried, sad or unhappy," "you are a bit worried, sad or unhappy" and "you are very worried, sad or unhappy". For the purpose of this study, responses to this question were dichotomized into two groups: "not worried, sad or unhappy" and "a bit and very worried, sad or unhappy" due to the small number of children indicating they were very worried, sad or unhappy. For the sake of brevity, we refer to feelings of worry and sadness, or mood, throughout this paper.

Covariates

A parent survey provided information on socio-demographic characteristics, including household income and parental education. Student height and weight were measured by a trained evaluation assistant to determine weight status. Weight status (normal weight, overweight, obese) was defined using cut-offs established for children and youth by the International Obesity Task Force. (21) Physical activity level was determined from the student and parent surveys, based on questions from the Physical Activity Questionnaire for Children (PAQ-C), a valid and reliable tool for assessing physical activity level. (22) These questions formed a composite score from 1 (least active) to 6 (most active).

Statistical analysis

Multilevel logistic regression methods were used to examine the association of diet quality with feelings of worry, sadness or unhappiness. These regression methods generated odds ratios for a 10% change in diet quality score. All analyses were adjusted for energy intake and seven categorical variables: gender, household income, parental education, weight status, physical activity level, area of residence and year of data collection. Total energy intake (kcal/day) was controlled for in all analyses as per recommendations for food frequency data. (23) Missing values for these variables were considered as separate covariate categories in the regression models, but their estimates are not presented. Population weights were applied to yield provincial population estimates. Analyses were performed using Stata Statistical Software (Release 11).

RESULTS

Table 1 shows that 32% of students reported feeling a bit worried or sad and 3% of students reported feeling very worried or sad. In univariate analysis, feelings of being worried, sad or unhappy were more prevalent among girls than boys (42% vs. 29%), among children with low as compared to high physical activity (48% vs. 24%), and among obese as compared to normal weight children (42% vs. 35%).

Table 2 presents odds ratios adjusted for energy intake (Model 1), energy intake and socio-demographic characteristics (Model 2), and additionally adjusted for physical activity and body weight (Model 3), for the association of diet quality with feeling worried, sad or unhappy. Diet quality was significantly associated with these feelings: for a 10% increase in diet quality score, the odds of feeling worried, sad or unhappy decreased by approximately 10% (Model 3 (all students): 1-0.90 times 100%). Students with more varied and more adequate diets had significantly lower odds of having these feelings. Greater dietary balance was significantly associated with increased odds of feeling worried, sad or unhappy.

Gender-stratified results (Table 2) showed that better overall diet quality was significantly associated with lower odds of feeling worried, sad or unhappy in girls only. Moreover, the importance of dietary adequacy and moderation for these feelings was more pronounced in girls than in boys. Finally, for both boys and girls, greater dietary balance was associated with increased odds of feeling worried, sad or unhappy.

DISCUSSION

The current study is one of only a few that investigated the relationship between diet and mood in children. The findings are consistent with work that suggested a relationship between poor diet quality and mental health problems in children. (9-11,24)

Many youngsters experience depressive symptoms that do not meet criteria for a diagnosis, (13) that may in fact represent early markers for mental health problems in adulthood. (12,13) Ravens-Sieberer et al. (25) confirmed this by revealing a strong correlation of EQ-5DY responses with borderline and abnormal mental health problems using the same survey instrument (EQ-5D-Y) as was used in the current study. Our observation that 42% of girls and 29% of boys report some degree of feelings of being worried, sad or unhappy adds to the concern that subclinical markers for future mental health problems are very prevalent.

Two particular aspects of diet--variety and adequacy--were significantly associated with decreased feelings of worry or sadness in the current study. This suggests that exposing children to a variety of foods--particularly foods that provide the essential nutrients required for healthy development--can play an important role in reducing some of the negative feelings experienced by children. In our earlier work, better dietary variety was shown to reduce the probability of developing internalizing disorders in subsequent years, (10) which draws further attention to the importance of dietary variety. These findings are therefore important to public health decision makers tasked with improving mental well-being of youngsters and with preventing mental disorders. Dietary moderation captures excess consumption of fat, saturated fat, cholesterol and sodium, and was found to have no substantial or statistically significant associations with feelings of worry or sadness. (18) Dietary balance captures the balance in energy originating from carbohydrates, fat or protein and the balance in the fatty acid composition of the diet. (18) Contrary to expectations, a better dietary balance was significantly associated with increased odds of feeling worried, sad or unhappy. Further nutritional research is needed to clarify the importance of dietary balance for mental health and well-being.

The study revealed that girls reported more feelings of worry, sadness or unhappiness than boys, and the existence of gender differences in the relationship of diet quality with mood. Various factors may contribute to the gender differentials in the relationship between diet and mood. These include the effect of diet on maturation, (26) the fact that girls mature earlier than boys and that the prevalence of mood disorders increases once girls enter puberty. (27-29) In addition, female adolescents and adults are on average more likely to under-report dietary intake than their male counterparts, which may contribute to explaining the observed relationships between diet and mood. (30-34)

There are several plausible biological mechanisms linking nutrition and mental well-being. Some studies have revealed that diets low in magnesium or high in glycemic load may lead to higher plasma C-reactive protein levels. C-reactive protein is a marker of low-grade inflammation and inflammation is considered to facilitate the development of depression. (35,36) A western diet typically has a high glycemic index (37) and a low magnesium content. (38) Other studies have suggested the involvement of oxidative stress in several mental illnesses, including schizophrenia, bipolar disorder, depression and autism. (39) Oxidative stress may induce neuronal damage, modulates intracellular signaling and ultimately leads to neuronal death. (39) Regular consumption of foods rich in antioxidants, for example blueberries, grapes, apples, and spinach, is demonstrated to have an inverse association with age-associated pathophysiological and cognitive changes. (40) There is evidence from animal studies that supplementation with extracts from these foods reduces or blocks neuronal death, which further suggests that interventions that promote healthy eating may reduce the public health burden of mental health disorders. (39)

Limitations to this study should be noted. The cross-sectional study design does not rule out the potential for reverse causality. It may be that children feeling worried, sad or unhappy eat less healthy foods. Both diet quality and feelings of worry, sadness and unhappiness were self-reported, which is prone to error. In addition, the outcome for this study was a single question about feeling worried, sad, or unhappy, drawn from the EQ-5D-Y. However, other studies using one or two questions have shown to be effective at identifying depression. (41-43) Also the EQ-5D-Y has been shown to be adequate for identifying individuals with depression and anxiety, (44) but EQ-5D-Y is not considered a diagnostic tool. Future studies examining diet and mental health may benefit from using a more sophisticated questionnaire in the assessment of depression and anxiety.

Despite these limitations, this study had several methodological strengths. For instance, this was a population-based study with a relatively high response rate, as well as a large sample size. Also, several socio-demographic and other factors were controlled for in the analysis, allowing for a clearer interpretation of the role of diet quality for the children's feelings, although we cannot exclude the presence of residual confounding and influences of unmeasured confounders. For example, children in settings that are not ideal for diet or mental health have both poor diet and mental health.

Mental health disorders result in substantial economic costs to society in addition to personal costs. Depression costs the Canadian economy more than $14 billion per year. (45) The findings from the current study suggest that diet quality plays an important role for mental health in addition to physical health. We recommend that consideration be given to diet quality as a preventive strategy to improve both mental and physical health.

Acknowledgement: The authors thank the grade 5 students, parents and schools for their participation in the REAL Kids Alberta evaluation. Thanks also to the evaluation assistants, health promotion coordinators and all others involved in the execution of the data collection, as well as Connie Lu for data validation and management. This research was funded through a contract with Alberta Health and through a Canada Research Chair in Population Health and Alberta Innovates Health Solutions Scholarship to Dr. Paul J. Veugelers. All interpretations and opinions in this article are those of the authors.

Conflict of Interest: None to declare.

REFERENCES

(1.) Government of Canada. The Human Face of Mental Health and Mental Illness in Canada, 2006. Available at: http://www.phac- aspc.gc.ca/publicat/human-humain06/ (Accessed April 24, 2011).

(2.) Ebbeling CB, Pawlak DB, Ludwig DS. Childhood obesity: Public-health crisis, common sense cure. Lancet 2002; 360(9331):473-82.

(3.) Lobstein T, Baur L, Uauy R. Obesity in children and young people: A crisis in public health. Obes Rev 2004; 5(Suppl 1):4-104.

(4.) Must A, Strauss RS. Risks and consequences of childhood and adolescent obesity. Int J Obes Relat Metab Disord 1999; 23(Suppl 2):S2-S11.

(5.) Akbaraly TN, Brunner EJ, Ferrie JE, Marmot MG, Kivimaki M, Singh-Manoux A. Dietary pattern and depressive symptoms in middle age. Br J Psychiatry 2009; 195(5):408-13.

(6.) Jacka FN, Pasco JA, Mykletun A, Williams LJ, Hodge AM, O'Reilly SL, et al. Association of western and traditional diets with depression and anxiety in women. Am J Psychiatry 2010; 167(3):305-11.

(7.) Sanchez-Villegas A, Delgado-Rodriguez M, Alonso A, Schlatter J, Lahortiga F, Serra Majem L, et al. Association of the Mediterranean dietary pattern with the incidence of depression: The Seguimiento Universidad de Navarra/University of Navarra follow-up (SUN) cohort. Arch Gen Psychiatry 2009; 66(10):1090-98.

(8.) McMartin SE, Jacka FN, Colman I. The association between fruit and vegetable consumption and mental health disorders: Evidence from five waves of a national survey of Canadians. Prev Med 2013; 56(3-4):225-30.

(9.) Jacka FN, Kremer PJ, Berk M, de Silva-Sanigorski AM, Moodie M, Leslie ER, et al. A prospective study of diet quality and mental health in adolescents. Plos One 2011; 6(9):e24805.

(10.) McMartin SE, Kuhle S, Colman I, Kirk SF, Veugelers PJ. Diet quality and mental health in subsequent years among Canadian youth. Public Health Nutr 2012; 15(12):2253-58.

(11.) Oddy WH, Robinson M, Ambrosini GL, O'Sullivan TA, de Klerk NH, Beilin LJ, et al. The association between dietary patterns and mental health in early adolescence. Prev Med 2009; 49(1):39-44.

(12.) Aalto-Setala T, Marttunen M, Tuulio-Henriksson A, Poikolainen K, Lonnqvist J. Depressive symptoms in adolescence as predictors of early adulthood depressive disorders and maladjustment. Am J Psychiatry 2002; 159(7):1235-37.

(13.) Pine DS, Cohen E, Cohen P, Brook J. Adolescent depressive symptoms as predictors of adult depression: Moodiness or mood disorder? Am J Psychiatry 1999; 156(1):133-35.

(14.) Fung C, Kuhle S, Lu C, Purcell M, Schwartz M, Storey K, et al. From "best practice" to "next practice": The effectiveness of school-based health promotion in improving healthy eating and physical activity and preventing childhood obesity. Int J Behav Nutr Phys Act 2012; 9(1):27.

(15.) Willett WC. Nutritional Epidemiology, 2nd ed. New York, NY: Oxford University Press, 1998; 321-46.

(16.) 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(3):336-40.

(17.) Health Canada. Food and Nutrition: The Canadian Nutrient File, 2007. Available at: http://www.hc-sc.gc.ca/fn-an/nutrition/fiche-nutri-data/cnf_ aboutus-aproposdenous_fcen-eng.php (Accessed October 27, 2010).

(18.) Kim S, Haines PS, Siega-Riz AM, Popkin BM. The Diet Quality Index- International (DQI-I) provides an effective tool for cross-national comparison of diet quality as illustrated by China and the United States. J Nutr 2003; 133(11):3476-84.

(19.) Patterson RE, Haines PS, Popkin BM. Diet quality index: Capturing a multidimensional behavior. J Am Diet Assoc 1994; 94(1):57-64.

(20.) Wille N, Badia X, Bonsel G, Burstrom K, Cavrini G, Devlin N, et al. Development of the EQ-5D-Y: A child-friendly version of the EQ-5D. Qual Life Res 2010; 19(6):875-86.

(21.) Cole TJ, Bellizzi MC, Flegal KM, Dietz WH. Establishing a standard definition for child overweight and obesity worldwide: International survey. BMJ2000; 320(7244):1240-43.

(22.) Crocker PR, Bailey DA, Faulkner RA, Kowalski KC, McGrath R. Measuring general levels of physical activity: Preliminary evidence for the Physical Activity Questionnaire for Older Children. Med Sci Sports Exerc 1997; 29(10):1344-49.

(23.) Willett WC, Howe GR, Kushi LH. Adjustment for total energy intake in epidemiologic studies. Am J Clin Nutr 1997; 65(4):S1220-S1228.

(24.) Jacka FN, Kremer PJ, Leslie ER, Berk M, Patton GC, Toumbourou JW, et al. Associations between diet quality and depressed mood in adolescents: Results from the Australian Healthy Neighbourhoods Study. Aust N Z J Psychiatry 2010; 44(5):435-42.

(25.) Ravens-Sieberer U, Wille N, Badia X, Bonsel G, Burstrom K, Cavrini G, et al. Feasibility, reliability, and validity of the EQ-5D-Y: Results from a multinational study. Qual Life Res 2010; 19(6):887-97.

(26.) de Ridder CM, Thijssen JH, Van 't Veer P, van Duuren R, Bruning PF, Zonderland ML, et al. Dietary habits, sexual maturation, and plasma hormones in pubertal girls: A longitudinal study. Am J Clin Nutr 1991; 54(5):805 13.

(27.) Hyde JS, Mezulis AH, Abramson LY. The ABCs of depression: Integrating affective, biological, and cognitive models to explain the emergence of the gender difference in depression. Psychol Rev 2008; 115(2):291-313.

(28.) Wade TJ, Cairney J, Pevalin DJ. Emergence of gender differences in depression during adolescence: National panel results from three countries. J Am Acad Child Adolesc Psychiatry 2002; 41(2):190-98.

(29.) Angold A, Costello EJ, Worthman CM. Puberty and depression: The roles of age, pubertal status and pubertal timing. Psychol Med 1998; 28(1):51-61.

(30.) Johansson L, Solvoll K, Bjorneboe GE, Drevon CA. Under- and over-reporting of energy intake related to weight status and lifestyle in a nationwide sample. Am J Clin Nutr 1998; 68(2):266-74.

(31.) Livingstone MB, Black AE. Markers of the validity of reported energy intake. J Nutr 2003; 133(Suppl 3):895S-920S.

(32.) Livingstone MBE, Prentice AM, Coward WA, Strain JJ, Black AE, Davies PSW, et al. Validation of estimates of energy-intake by weighed dietary record and diet history in children and adolescents. Am J Clin Nutr 1992; 56(1):29-35.

(33.) Murakami K, Miyake Y, Sasaki S, Tanaka K, Arakawa M. Characteristics of under- and over-reporters of energy intake among Japanese children and adolescents: The Ryukyus Child Health Study. Nutrition 2012; 28(5):532-38.

(34.) Vance VA, Woodruff SJ, McCargar LJ, Husted J, Hanning RM. Self-reported dietary energy intake of normal weight, overweight and obese adolescents. Public Health Nutr 2009; 12(2):222-27.

(35.) King DE, Mainous AG, Geesey ME, Woolson RF. Dietary magnesium and C-reactive protein levels. J Am Coll Nutr 2005; 24(3):166-71.

(36.) Liu SM, Manson JE, Buring JE, Stampfer MJ, Willett WC, Ridker PM. Relation between a diet with a high glycemic load and plasma concentrations of high- sensitivity C-reactive protein in middle-aged women. Am J Clin Nutr 2002; 75(3):492-98.

(37.) Bell AC, Kremer PJ, Magarey AM, Swinburn BA. Contribution of 'noncore' foods and beverages to the energy intake and weight status of Australian children. Eur J Clin Nutr 2005; 59(5):639-45.

(38.) Ford ES, Mokdad AH. Dietary magnesium intake in a national sample of US adults. J Nutr 2003; 133(9):2879-82.

(39.) Jacka F, Berk M. Food for thought. Acta Neuropsychiatrica 2007; 19(5):321- 23.

(40.) Joseph JA, Shukitt-Hale B, Denisova NA, Prior RL, Cao G, Martin A, et al. Long-term dietary strawberry, spinach, or vitamin E supplementation retards the onset of age-related neuronal signal-transduction and cognitive behavioral deficits. J Neurosci 1998; 18(19):8047-55.

(41.) Chochinov HM, Wilson KG, Enns M, Lander S. "Are you depressed?" Screening for depression in the terminally ill. Am J Psychiat 1997; 154(5):674- 76.

(42.) Huffman JC, Smith FA, Blais MA, Beiser ME, Januzzi JL, Fricchione GL. Rapid screening for major depression in post-myocardial infarction patients: An investigation using Beck Depression Inventory II items. Heart 2006; 92(11):1656-60.

(43.) McManus D, Pipkin SS, Whooley MA. Screening for depression in patients with coronary heart disease (data from the heart and soul study). Am J Cardiol 2005; 96(8):1076-81.

(44.) Johnson JA, Supina AL, Patten SB, Williams JVA, Maxwell CJ. The usefulness of the EQ-5D in differentiating among persons with major depressive episode and anxiety. Qual Life Res 2007; 16(5):749-54.

(45.) Stephens T, Joubert N. The economic burden of mental health problems in Canada. Chronic Dis Can 2001; 22(1):18-23.

Received: January 24, 2013

Accepted: July 24, 2013

Seanna E. McMartin, MSc, [1,2] Noreen D. Willows, PhD, [3] Ian Colman, PhD, [2] Arto Ohinmaa, PhD, [1] Kate Storey, PhD, [1] Paul J. Veugelers, PhD [1]

Author Affiliations

[1.] Department of Public Health Sciences, School of Public Health, University of Alberta, Edmonton, AB

[2.] Department of Epidemiology and Community Medicine, University of Ottawa, Ottawa, ON

[3.] Department of Agriculture, Food, and Nutritional Science, University of Alberta, Edmonton, AB

Correspondence: Dr. Paul Veugelers, Department of Public Health Sciences, School of Public Health, University of Alberta, 3-50 University Terrace, 8303--112 Street, Edmonton, AB T6G 2T4, Tel: 780-495-9095, Fax: 780-492-5521, E-mail: [email protected]

Table 1. Socio-demographic and Self-reported Feelings of
Worry, Sadness and Unhappiness Among Grade 5
Students in Alberta

                             % of Grade 5    % Reporting Feeling
                               Students     Worried, Sad or Unhappy
                                            No    A Bit     Very
Sex
  Female                          51        58      38       4
  Male                            49        71      27       2
Household income ($)
  <50,000                         16        62      34       4
  50,001-75,000                   12        63      33       4
  75,001-100,000                  14        66      31       3
  >100,001                        25        66      31       3
  Not reported                    33
Parental education
  Secondary school or less        24        62      34       4
  College                         37        64      32       3
  University                      33        66      31       2
  Not reported                    5
Residence
  Metropolitan area               47        64      33       3
  City                            39        65      32       4
  Rural/town                      14        64      32       3
Year of data collection
2008                              50        62      35       3
2010                              50        66      30       4
Physical activity level
  Low level                       3         53      44       4
  Medium                          87        63      33       3
  High level                      10        76      22       2
Body weight status
  Normal weight                   72        65      32       3
  Overweight, not obese           20        64      32       4
  Obese                           8         58      38       4

Table 2. Odds Ratios (OR) With 95% Confidence Intervals for the
Association Between Indicators of Diet Quality and Feeling a Bit/Very
Worried, Sad or Unhappy

                  Model 1 *       Model 2 ([dagger])
                 OR (95% CI)         OR (95% CI)

Diet quality   0.92 (0.86-0.98)   0.89 (0.84-0.96)
Variety        0.95 (0.92-0.99)   0.94 (0.91-0.98)
Adequacy       0.90 (0.84-0.96)   0.87 (0.82-0.93)
Moderation     0.96 (0.92-1.01)   0.95 (0.91-1.00)
Balance        1.06 (1.02-1.09)   1.05 (1.02-1.09)

                                  Model 3 ([double dagger])
                                    OR (95% CI)
               All Students       Boys               Girls
Diet quality   0.90 (0.85-0.97)   0.94 (0.86-1.03)   0.89 (0.80-0.98)
Variety        0.95 (0.91-0.98)   0.93 (0.88-0.99)   0.96 (0.91-1.02)
Adequacy       0.89 (0.83-0.95)   0.91 (0.83-1.00)   0.87 (0.80-0.95)
Moderation     0.96 (0.91-1.00)   0.99 (0.94-1.05)   0.93 (0.87-0.99)
Balance        1.05 (1.02-1.09)   1.06 (1.01-1.11)   1.04 (1.00-1.09)

OR: odds rate ratio; CI: confidence interval.

All analyses weighted to yield provincial population estimates.

* Adjusted for energy intake.

([dagger]) Adjusted for energy intake, gender, household
income, parental education, geographic area, and year of
data collection.

([double dagger]) Adjusted for energy intake, gender, household
income, parental education, geographic area, year of data
collection, body weight status and physical activity level.