Original Article

European Journal of Clinical Nutrition (2007) 61, 822–829; doi:10.1038/sj.ejcn.1602601; published online 24 January 2007

Eating styles, overweight and obesity in young adult twins

A Keski-Rahkonen1,2,3, C M Bulik4, K H Pietiläinen2,3, R J Rose5, J Kaprio2,6 and A Rissanen3

  1. 1Mailman School of Public Health, Department of Epidemiology, Columbia University, New York, NY, USA
  2. 2Department of Public Health, University of Helsinki, Finland
  3. 3Obesity Research Unit, Department of Psychiatry, Helsinki University Central Hospital, Helsinki, Finland
  4. 4Department of Psychiatry, University of North Carolina at Chapel Hill, North Carolina, USA
  5. 5Department of Psychology, Indiana University, Bloomington, Indiana, USA
  6. 6Department of Mental Health, National Public Health Institute, Helsinki, Finland

Correspondence: Dr A Keski-Rahkonen, Department of Epidemiology, Columbia University, School of Public Health, 722 W. 168th Street, 7th Floor, Room # 720-F, New York, NY 10032, USA. E-mail: anna.keski-rahkonen@helsinki.fi

Received 19 January 2006; Revised 26 October 2006; Accepted 26 October 2006; Published online 24 January 2007.

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Abstract

Objective:

 

To explore the association of eating styles with overweight and obesity in young adults, controlling for identical genetic background in monozygotic twins.

Design:

 

Prospective twin cohort study.

Setting:

 

Finland, 1991–2002.

Subjects:

 

Two-hundred and thirty-three women and 2060 men from the FinnTwin16 study, aged 16 years at baseline (T1), and ranging from 22 to 27 years at the time of the nutritional assessment (T4).

Methods:

 

Eating styles (Restrictive/overeating, health-conscious, snacking, emotional and externally induced), self-reported at T4, were contrasted with body mass indices (BMIs) at T1 and T4.

Results:

 

At T4, obesity (BMIgreater than or equal to30Kg/m2) was significantly cross-sectionally associated with restrictive eating, frequent snacks, eating in the evening, avoiding fatty foods and failure to maintain healthy eating patterns. These associations were independent of BMI at T1. Obese women self-reported more vulnerability to external eating cues and comfort eating than normal-weight women. However, in a multivariable model, only restrictive/overeating and health-conscious eating styles were significant correlates of obesity at T4, independent of gender and BMI at T1. When we controlled for genetic background restricting the analysis to the 39 female and 45 male monozygotic twin pairs discordant for obesity or overweight (BMIgreater than or equal to25Kg/m2), restrictive/overeating eating style was still statistically significantly associated with excess weight.

Conclusions:

 

The eating styles of obese young adults differ from their normal-weight counterparts: restrictive eating, overeating and fewer healthy food choices are associated with obesity. Different eating styles may partially explain weight differences in individuals with identical genetic background.

Keywords:

eating styles, emotional eating, external eating, body mass index, cohort study

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Introduction

Various theoretical approaches have attempted to explain obesity in humans. Although body size and composition are strongly genetically determined (Maes et al., 1997), genetic influences alone cannot explain the recent rapid rise in rates of obesity. More environmentally influenced eating behaviors (Neale et al., 2003; de Castro, 2004), such as individual eating styles, may thus have an important triggering role in excessive weight gain.

Over time, researchers have proposed several models of how eating styles could lead to obesity (Rodin et al., 1989; van Strien and Ouwens, 2003). Indeed, given the changing topography of food availability and composition, the applicability of various models may be changing over time. According to the psychosomatic model of obesity, anxiety and psychological stress are reduced by overeating. (Kaplan and Kaplan, 1957; van Strien and Ouwens, 2003). The internal/external hypothesis (Schachter and Rodin, 1974; van Strien and Ouwens, 2003) posits an alternative approach: people at normal weight have learned to interpret physiological hunger signals correctly, but obese people lack that understanding and depend to a greater degree on external cues both to initiate and stop eating. If true, a proportion of the population is excessively vulnerable to external influences on eating, such as sights and smells of food or advertising. Yet another attempt to explain obesity is the restraint theory (Herman and Mack, 1975), suggesting that the key factor in producing and maintaining overeating is chronic dieting: feelings of deprivation and physical hunger associated with dieting prompt episodes of overeating and gaining weight. Finally, the ecological association of increases in snacking (Zizza et al., 2001; Männistö et al., 2003; Berteus et al., 2005) and increased rates of obesity may suggest that a snacking eating style, that is, eating characterized by high-energy food and drinks between meals, may contribute to obesity risk (Booth, 1988; Berteus et al., 2005).

These four theories each predict different eating styles. The psychosomatic theory predicts an emotional eating style, the internal/external hypothesis predicts an external eating style (i.e. eating prompted by visual or olfactory cues or advertisements), the restraint theory predicts a restrictive eating style, and the Booth hypothesis predicts a snacking eating style. Each theory hypothesizes that overeating mediates the effect of eating style on becoming overweight. Inversely, adherence to healthful eating styles (avoiding excessive calorie intake and excessive dieting) should protect against obesity.

Although the role of eating styles in obesity has been questioned by some earlier research (Rodin et al., 1989; Allison and Heshka, 1993), others have suggested that earlier research may have underestimated the role of individual behaviors and that further investigation is still necessary, particularly on the population level (Lluch et al., 2000; Wardle et al., 2001; Caccialanza et al., 2004; Berteus et al., 2005). In this study, we tested whether individual eating styles are associated with overweight and obesity in a population sample of young adult twins. To control for genetic background, we also explored these patterns in a subsample of monozygotic twins.

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Methods

Participants

The data reported are from FinnTwin16, a population-based study of five birth cohorts of Finnish twins born between 1975 and 1979 (Kaprio et al., 2002). Data collection was submitted to and approved by local ethics committees. The baseline assessment was conducted by postal questionnaire at the age of 16 years (T1), with follow-ups at 17 years (T2), 18.5 years (T3) and at 22–27 years (T4). At T4, each birth cohort of the twins were contacted semiannually between the year 2000 and 2002, and the respondent's mean age was 24.4 years. The questionnaires assessed personality, social relationships, general health and health habits. The present study is based on responses at T1 and T4, comprising 4667 twins (2545 females and 2122 males). Response rates were high (>85%) across all occasions.

Twins' zygosity was determined by standard items included in the baseline questionnaire (Sarna et al., 1978; Sarna and Kaprio, 1980) and was, when necessary, supplemented with photographs, fingerprints, and DNA-marker studies. The twin pairs were classified as monozygotic (MZ), dizygotic (DZ) or unknown zygosity. The number of twin pairs where the zygosity of both twins was known was 2009.

We excluded individuals (N=251, 5.4%) who self-reported potentially weight-affecting chronic diseases at T4: anorexia and bulimia nervosa; diabetes; inflammatory bowel disease, chronic diarrhoea, celiac disease; hypo- or hyperthyroidism, lupus, mental retardation, malignancies, cerebral palsy and other mobility disorders. At T4, information on body mass index (BMI) was incomplete for 23 individuals. Thus, the final sample comprised 4393 healthy individuals (2333 women and 2060 men). The subsample of MZ twins included 358 female and 242 male twin pairs.

Main outcome variables

BMI and overweight
 

BMI (kg/m2) was calculated based on the twins' self-reported weight and height at T1 and T4. Agreement between self-reported weight and measured weight in a subsample of this cohort at T4 was 0.96 and 0.94 respectively (Schousboe et al., 2003; Silventoinen et al., 2003). As the dependent variable in the polytomous logistic regression models, BMI at T4 was categorized as follows: normal weight (BMI<25 Kg/m2), mild overweight (25less than or equal to BMI<27 Kg/m2), moderate overweight (27less than or equal toBMI<30Kg/m2), and obesity (BMIgreater than or equal to30 Kg/m2). BMI at T1, a predictor of T4 in the models, was used as a continuous variable. In the pairwise analyses, MZ pairs discordant for obesity or overweight (BMIgreater than or equal to25 Kg/m2) were used, because there were few MZ pairs discordant for obesity (BMIgreater than or equal to30 Kg/m2).

Eating styles
 

To assess eating styles of the twins at T4, we used a questionnaire previously developed by us (Keski-Rahkonen et al., 2005) that addressed restrictive/overeating, snacking, health-conscious, emotional, and externally induced eating styles (see Appendix A). Participants were asked to choose the one of four options that best characterized their overall eating style (Appendix, item A). Subsequently, five items assessed snacking/grazing styles, three health-conscious eating, two emotional eating, and one externally cued eating (Appendix, items B): responses to the latter items were dichotomized. Because the internal consistency of multiple item assessment of eating styles was relatively low (Cronbach's alphasless than or equal to0.70), each item was used as a separate variable in the analyses, but their groupings are based on factor analysis that had similar solutions in both genders (further details about validation and factor analyses available from the first author).

Statistical analyses

We investigated differences between eating styles and BMI and overweight/obesity categories using cross-tabulations, the Pearson chi2 test of independence, linear and logistic regression, all corrected for clustered sampling within twin pairs using the svytab, svyreg and cluster procedures in Stata 8.0. The relationship of categorical BMI at T4 and eating styles at T4 was assessed using polytomous logistic regression models (Hosmer and Lemeshow, 2000), controlling for BMI at T1 and correcting for clustered sampling. The four categories of BMI were used as outcome variables, individuals at normal weight (BMI<25 Kg/m2) being the reference category. In a multiple logistic regression model that controlled for gender and BMI at T1, we entered all the eating styles in the model, testing which of them remained significantly associated with obesity. The correlations of the independent variables in the model did not exceed r=0.4.

In twin analyses, we computed Pearson and polychoric correlation coefficients to assess intrapair twin resemblance by zygosity group. Monozygotic twin pairs were also compared using conditional logistic regression. Stata 8.0 was used for all analyses.

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Results

Relation between obesity and eating styles

The prevalence of obesity (BMIgreater than or equal to30 Kg/m2) at T4 was 3.9% in women and 4.1% in men, which did not differ significantly (P=0.62). Overweight (25less than or equal toBMI<30 Kg/m2) at T4 was more common in men (24.6%) than in women (11.5%, P<0.0001). Conversely, restrictive eating, overeating, and alternating restricting/overeating at T4 were significantly more common in women than in men (P<0.00001), and significantly more common among the obese than the non-obese (Table 1). The frequencies of eating styles by sex, and the mean BMI and proportion of obese participants per each eating style category are presented Tables 1 and 2. The frequencies of different eating styles exhibited clear sex differences in all other areas except eating in the evening and eating while watching TV.



As detailed in Table 3, individuals overweight or obese at T4 had a lower likelihood of attempting to maintain healthy eating styles than their normal-weight peers. Restrictive eating, snacking between meals, consuming food and snacks in the evening and avoiding fatty foods were associated with obesity in both men and women. In contrast to women at normal weight and men at all weights, obese women were much more likely to comfort themselves with food. However, both obese women (BMIgreater than or equal to30 Kg/m2) and overweight men (BMI 27–29.9Kg/m2) were significantly more likely to be prompted to eat by visual cues than their normal-weight peers. All these associations were independent of the participants' BMI at T1.


Multivariable models

When all the eating styles were entered in a multivariable model predicting obesity, controlling for gender and BMI at T1 (Table 4), restricting/overeating eating style at T4 was associated with obesity at T4 and health-conscious eating style at T4 decreased the risk of obesity at T4.


Twin aspects of eating styles

Pairwise twin correlations of eating styles are detailed in Table 5. The intrapair correlations for BMI were higher than those for eating styles in same-sex MZ and DZ and opposite-sex twin pairs. In a conditional logistic regression model of female MZ twin pairs discordant for obesity or overweight (BMIgreater than or equal to25 Kg/m2, N=39) at T4, the risk of restrictive eating in the overweight was 6.9 (95% CI: 1.2–38.8) times greater and the risk of overeating was 7.8 (95% CI: 1.1–54.4) times greater than that of the non-overweight twin. Among male MZ twin pairs discordant for overweight (N=45), the risk of restrictive eating in the overweight was 4.8 (95% CI: 1.2–18.5) times that of the non-overweight twin. Other eating styles were not statistically significantly associated with overweight in either gender when controlling for common genetic background.


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Discussion

In this population-based study, various eating styles, particularly those characterized by restrictive eating/overeating, snacking between meals, and grazing throughout the evening, were associated with excess weight in young adults, even when controlling for their weight in late adolescence. Conversely, young adults who reported attempting to maintain healthy eating patterns were very significantly less likely to be overweight or obese than those who did not report such attempts. Specific attempts to avoid fatty foods and calories, however, were more likely in the obese than in the non-obese.

Restrictive/overeating eating styles increased the risk of obesity, and health-conscious eating styles decreased the risk of obesity. In multivariable models, the possible influence of other eating styles on weight appeared to be mediated through restrictive/overeating and health-conscious eating styles, as we hypothesized. Although we confirmed the previous observations that snacking is associated with obesity in both sexes (Berteus et al., 2005), that emotional eating is positively correlated with BMI in women but not in men (Lluch et al., 2000), and that the reactivity to external food-related signals is not only characteristic of children (Lluch et al., 2000) but also of young adults, these associations seemed secondary in importance and mediated by restrictive/overeating eating styles. Indeed, several earlier studies have reported the coexistence of high dietary restraint with overweight and obesity in children, adolescents and adults (Braet and Wydhooge, 2000; Lluch et al., 2000).

Although this study could not tease out the causal relationship between eating styles and obesity, some clues were provided by our data. First, when our analyses controlled for BMI at T1, eating styles and obesity were nevertheless strongly associated. Second, genetically identical female and male MZ twins who were discordant for overweight were also statistically significantly more likely to be discordant for restrictive eating styles. Obesity and eating styles would be less likely to be causally related had the twins been discordant for BMI, but not discordant for restrictive eating styles. Third, MZ and DZ twins were less likely to have similar eating styles than similar BMIs. Conceivably, although body weight and size appear strongly genetically influenced (Maes et al., 1997; Keski-Rahkonen et al., 2005), in MZ twin pairs who develop BMI discordance, more environmental sources of influences, such as eating styles, may be responsible. Thus, a genetic predisposition constitutes the foundation of weight regulation, but more environmentally influenced behavioral patterns, such as eating styles, explain why genetically identical individuals are phenotypically dissimilar.

Our finding thus underscores the importance of future studies on the interaction of genes and environment in obesity related phenotypes. The obvious next step is to quantify the magnitude and direction of genetic and environmental contributions to various eating styles and nutritional patterns and their relation to BMI, as well as to design studies to identify specific genes that code for proteins that may influence these behaviors.

The strengths of this study include its large sample size and good coverage of the Finnish young adult population. Because of excellent response rates and nationwide sampling, the education level of our study population at 17 years corresponded relatively well to that of the 17–18-y-old Finnish population (Haven, 1998), albeit with some bias towards higher education in our participants.

There are also some further limitations to this study. Of the T1 participants, about 14.5% had been lost to follow-up by T4. Nonresponse was significantly more common among men and individuals of unknown education level, although there were no statistically significant differences between responders and nonresponders in their family socioeconomic status (Penninkilampi-Kerola et al., 2005). Due to nonresponse and exclusion of individuals with weight-affecting illnesses, obesity is likely underestimated in our sample, particularly among men. Conversely, because the greater muscularity of young men may be a confounder when BMI is used to measure overweight, we observed much higher prevalences of overweight among our men than among our women despite almost identical prevalences of obesity. Although the prevalences reported here were lower than those in the UK and USA (Hedley et al., 2004; Rennie and Jebb, 2005), and also lower than prevalences reported among Finnish adults (Lahti-Koski et al., 2002), we believe that this sample provides valuable information about a population where obesity is rapidly increasing (Kautiainen et al., 2002).

Inherent to all self-report-based approaches to dietary questions, self-reporting bias is likely in this study: measures of eating styles were entirely subjective. Societal pressures may cause women to assess their eating styles more critically than do men, which may inflate gender differences observed in this study. In the absence of further information about actual energy intake, it is difficult to further assess these potential biases.

Eating styles of obese young adults differ markedly from their normal weight counterparts, with clear sex differences. As patterns of restrictive eating, overeating, and alternating restrictive/overeating were most commonly associated with obesity, factors that lead to the development and maintenance of these types of eating styles warrant further investigation as we bolster efforts to prevent the development of obesity across the lifespan. This study also implies that genetic predisposition alone does not dictate body weight: environmentally influenced behavioral patterns, such as eating styles and healthful food choices, also make a difference and merit further study.

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References

  1. Allison DB, Heshka S (1993). Emotion and eating in obesity? A critical analysis. Int J Eat Disord 13, 289–295. | Article | PubMed | ChemPort |
  2. Berteus FH, Torgerson JS, Sjostrom L, Lindroos AK (2005). Snacking frequency in relation to energy intake and food choices in obese men and women compared to a reference population. Int J Obes (Relat Metab Disord Lond) 29, 711–719. | Article |
  3. Booth DA (1988). Mechanisms from models – actual effects from real life: the zero-calorie drink-break option. Appetite 11 (Suppl 1), 94–102. | PubMed |
  4. Braet C, Wydhooge K (2000). Dietary restraint in normal weight and overweight children. A cross-sectional study. Int J Obes Relat Metab Disord 24, 314–318. | Article | PubMed | ChemPort |
  5. Caccialanza R, Nicholls D, Cena H, Maccarini L, Rezzani C, Antonioli L, et al. (2004). Validation of the Dutch Eating Behaviour Questionnaire parent version (DEBQ-P) in the Italian population: a screening tool to detect differences in eating behaviour among obese, overweight and normal-weight preadolescents. Eur J Clin Nutr 58, 1217–1222. | Article | PubMed | ChemPort |
  6. de Castro JM (2004). Genes, the environment and the control of food intake. Br J Nutr 92 (Suppl 1), S59–S62. | Article | PubMed | ChemPort |
  7. Haven H (1998). Koulutus Suomessa [Education in Finland]. Koulutus 1, 61.
  8. Hedley AA, Ogden CL, Johnson CL, Carroll MD, Curtin LR, Flegal KM (2004). Prevalence of overweight and obesity among US children, adolescents, and adults, 1999–2002. JAMA 291, 2847–2850. | Article | PubMed | ISI | ChemPort |
  9. Herman CP, Mack D (1975). Restrained and unrestrained eating. J Pers 43, 647–660. | Article | PubMed | ChemPort |
  10. Hosmer DW, Lemeshow S (2000). Applied logistic regression 2nd ed. Wiley: New York.
  11. Kaplan HI, Kaplan HS (1957). The psychosomatic concept of obesity. J Nerv Ment Dis 125, 181–201. | PubMed | ChemPort |
  12. Kaprio J, Pulkkinen L, Rose RJ (2002). Genetic and environmental factors in health-related behaviors: studies on Finnish twins and twin families. Twin Res 5, 366–371. | Article | PubMed |
  13. Kautiainen S, Rimpelä A, Vikat A, Virtanen SM (2002). Secular trends in overweight and obesity among Finnish adolescents in 1977-1999. Int J Obes Relat Metab Disord 26, 544–552. | Article | PubMed | ChemPort |
  14. Keski-Rahkonen A, Neale BM, Bulik CM, Pietilainen KH, Rose RJ, Kaprio J et al. (2005). Intentional weight loss in young adults: sex-specific genetic and environmental effects. Obes Res 13, 745–753. | PubMed |
  15. Lahti-Koski M, Pietinen P, Heliövaara M, Vartiainen E (2002). Associations of body mass index and obesity with physical activity, food choices, alcohol intake, and smoking in the 1982-1997 FINRISK Studies. Am J Clin Nutr 75, 809–817. | PubMed | ISI | ChemPort |
  16. Lluch A, Herbeth B, Mejean L, Siest G (2000). Dietary intakes, eating style and overweight in the Stanislas Family Study. Int J Obes Relat Metab Disord 24, 1493–1499. | Article | PubMed | ChemPort |
  17. Maes HH, Neale MC, Eaves LJ (1997). Genetic and environmental factors in relative body weight and human adiposity. Behav Genet 27, 325–351. | Article | PubMed | ISI | ChemPort |
  18. Männistö S, Ovaskainen M-L, Valsta L (eds) (2003). Finravinto 2002 –tutkimus. [The National FINDIET 2002 Study]. Helsinki: Kansanterveyslaitoksen julkaisuja B3.
  19. Neale BM, Mazzeo SE, Bulik CM (2003). A twin study of dietary restraint, disinhibition and hunger: an examination of the eating inventory (three factor eating questionnaire). Twin Res 6, 471–478. | Article | PubMed | ISI |
  20. Penninkilampi-Kerola V, Kaprio J, Moilanen I, Rose RJ (2005). Co-twin dependence modifies heritability of abstinence and alcohol use: a population-based study of Finnish twins. Twin Res Hum Genet 8, 232–244. | Article | PubMed |
  21. Rennie KL, Jebb SA (2005). Prevalence of obesity in Great Britain. Obes Rev 6, 11–12. | Article | PubMed | ISI | ChemPort |
  22. Rodin J, Schank D, Striegel-Moore R (1989). Psychological features of obesity. Med Clin North Am 73, 47–66. | PubMed | ChemPort |
  23. Sarna S, Kaprio J (1980). Use of multiple logistic analysis in twin zygosity diagnosis. Hum Hered 30, 71–80. | PubMed | ChemPort |
  24. Sarna S, Kaprio J, Sistonen P, Koskenvuo M (1978). Diagnosis of twin zygosity by mailed questionnaire. Hum Hered 28, 241–254. | PubMed | ChemPort |
  25. Schachter S, Rodin J (1974). Obese humans and rats. Erlbaum/Halsted: Washington, DC.
  26. Schousboe K, Willemsen G, Kyvik KO, Mortensen J, Boomsma DI, Cornes BK et al. (2003). Sex differences in heritability of BMI: a comparative study of results from twin studies in eight countries. Twin Res 6, 409–421. | Article | PubMed | ISI |
  27. Silventoinen K, Sammalisto S, Perola M, Boomsma DI, Cornes BK, Davis C et al. (2003). Heritability of adult body height: a comparative study of twin cohorts in eight countries. Twin Res 6, 399–408. | Article | PubMed |
  28. van Strien T, Ouwens MA (2003). Counterregulation in female obese emotional eaters: Schachter, Goldman, and Gordon's (1968) test of psychosomatic theory revisited. Eat Behav 3, 329–340. | Article | PubMed |
  29. Wardle J, Guthrie C, Sanderson S, Birch L, Plomin R (2001). Food and activity preferences in children of lean and obese parents. Int J Obes Relat Metab Disord 25, 971–977. | Article | PubMed | ChemPort |
  30. Zizza C, Siega-Riz AM, Popkin BM (2001). Significant increase in young adults' snacking between 1977–1978 and 1994–1996 represents a cause for concern!. Prev Med 32, 303–310. | Article | PubMed | ChemPort |
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Appendices

Appendix A

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Acknowledgements

Data collection was supported by NIAAA grants AA12502 and AA08315, the European Union Fifth Framework Program (QLRT-1999-00916 and QLG2-CT-2002-01254), and the Academy of Finland (44069 and 201461). Data analysis was supported by the Psychiatric Epidemiology Training Program (MH013043), the State Endowment for Helsinki University Central Hospital (EVO), and the Yrjö Jahnsson, Jalmari and Rauha Ahokas, Helsingin Sanomat, Biomedicum and Finnish Cultural Foundations.

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