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Prevalence and correlates of self-reported disordered eating: A cross-sectional study among 90 592 middle-aged Norwegian women

  • Marie Sigstad Lande,

    Roles Formal analysis, Writing – original draft, Writing – review & editing

    Affiliation Department of Community Medicine, UiT The Arctic University of Norway, Tromsø, Norway

  • Jan H. Rosenvinge,

    Roles Supervision, Writing – review & editing

    Affiliation Department of Psychology, UiT The Arctic University of Norway, Tromsø, Norway

  • Guri Skeie,

    Roles Supervision, Writing – review & editing

    Affiliation Department of Community Medicine, UiT The Arctic University of Norway, Tromsø, Norway

  • Charlotta Rylander

    Roles Investigation, Supervision, Writing – original draft, Writing – review & editing

    Affiliation Department of Community Medicine, UiT The Arctic University of Norway, Tromsø, Norway


Disordered eating (DE) is extensively studied among adolescents and young women. However, there is growing evidence that DE as well as the clinical eating disorders may occur at any age from childhood to advanced years. This study aimed to determine the prevalence and correlates of DE in a representative sample of middle-aged women from Norway. The study included 90 592 women (median age: 55 years) from the Norwegian Women and Cancer study who responded to a questionnaire between the years 2002–2005. Correlates of self-reported DE were assessed by logistic regression analyses. The overall period prevalence of DE between 2002–2005 was 0.28 (95% confidence interval 0.25–0.31) %, and was highest among women ≥ 66 years: 0.65 (0.60–0.70) %. DE was strongly associated with depression (Odds ratio [OR] 3.34 [95% confidence interval 2.53–4.41]), being unemployed (OR 1.78 [1.32–2.40]) and single (OR 1.66 [1.25–2.20]). Women with DE were more likely to report low energy intake (OR 1.41 [1.08–1.86]) and were less likely to be moderately physically active (OR 0.67 [0.47–0.95]). Using the largest study sample in the literature, the present findings confirm smaller studies showing that DE do occur in women in mid-life and older age as well. Our results contribute to address a somewhat under-communicated community health problem that needs attention in terms of age-specific treatment and prevention.


Body dissatisfaction, weight preoccupation, and dysfunctional eating patterns represent the core features of disordered eating (DE). DE, as well as the diagnostic counterparts, anorexia nervosa (AN), bulimia nervosa (BN) and binge eating disorder (BED) have been conceptualized as juvenile problems in terms of etiology (e.g., pre-pubertal risk factors and developmental age specific challenges) and peak prevalence [1, 2]. However, there is growing evidence that DE as well as the clinical eating disorders may occur at any age from childhood to advanced years. Since 1986, several reviews of late onset DE have shown that also developmental challenges related to life transition issues in midlife may elicit DE [36]. High prevalence of DE features among older women has also been reported: In a study of 536 women aged 50–64 years, 27% were concerned about being too fat [7] and among a random sample of 1000 women aged 60–70 years, 60% reported body dissatisfaction [8]. Ng et al. reported a prevalence of 2.6% of DE among 2870 women above 50 years [9]. Another study by Runfola et al. found that body dissatisfaction was highly prevalent (72–93%) among adult women aged 35 to 75 and above, and with no age difference [10]. The latter study contrast other large (n = 1800–27 252) population studies [2, 1113], which found an inverse relationship between age and prevalence of eating disorders/DE. For instance, a population-based study of about 25 000 Norwegians from mid-Norway reported an overall prevalence of 12% of DE among women above 30 years in 2006–2008 and a negative association with age [13]. Previous studies have also suggested that the focus on thin female body ideals and concerns about being too fat seem to level off after the age of 60 [7, 14]. Thus, although DE is likely more prevalent among younger women, it is still a challenge for women in advanced years and often associated with serious comorbidities. DE in older adults has for instance been associated with higher BMI, and about six times increased risk of anxiety, mood disorders and alcohol dependence [7, 1520].

Across studies, DE is one of the most consistent risk factors for AN, BN, and BED [21]. Considering the fact that incident cases of BN and BED may emerge at ages above 50 [2], a monitoring of DE among adults in the general population is highly warranted in order to scale treatment and prevention efforts. Additionally, there is currently little information about the prevalence of DE among the general Norwegian female population above 40 years of age. Thus, the aim of the present study was to estimate the prevalence of DE in a representative sample of 90 592 Norwegian women and to explore sociodemographic and lifestyle-related correlates.


Study design and participants

The Norwegian Women and Cancer Study (NOWAC) is a national representative cohort study that was initiated in 1991, aiming to explore the associations between lifestyle factors and cancer among Norwegian women [22]. A random selection of women between the age of 30 and 70 years from the National Registry of Norway were invited to participate in the study through a letter with a detailed questionnaire sent to their home address. Those who agreed to participate have been followed up regularly with consecutive questionnaires every 6-7th year. The cohort has been expanded several times, and at present, it includes more than 170 000 Norwegian women and encompasses several other health outcomes than cancer. The NOWAC questionnaire includes questions about sociodemographic variables, self-reported health and lifestyle habits including use of various medications and a detailed food frequency questionnaire. The questionnaires have been distributed in waves, and some variables have been common in all waves, while other variables have varied depending on age groups and hypotheses. The external validity of the NOWAC study has been found to be satisfactory, with no major source of selection bias [23]. The NOWAC study has been approved by the Regional Committee for Medical Research Ethics in Northern Norway and the Norwegian Data Inspectorate. All participants gave their written informed consent.

The present study includes 90 592 women who answered a NOWAC questionnaire between the years 2002–2005 where a question related to eating disorders were included. Some women were first responders while others had answered at least one NOWAC questionnaire before. The response rate in NOWAC has varied between 48% (first responders) to 81% (second responders) [22]. No exclusion criteria were applied to the initial sample.

DE and covariates

Information about self-reported DE was extracted from the food frequency questionnaires, where the participants were asked to indicate whether any special conditions influenced their diet. The question was phrased “Does any of the following alternatives influence your diet? You can select more than one alternative”. The alternatives included: “I am a vegetarian; I do not follow a Norwegian diet; I am allergic; I have a chronic disease; I have anorexia; I have bulimia; I am trying to lose weight; Diet with low glycemic index”. If a participant did not select any of the above-mentioned alternatives, it was interpreted as “no”. Therefore, there was no missing information on this question and DE was defined as participants that indicated AN, BN, or both. There was no questions of other types of DE available.

The variables included in the present study were extracted from the same questionnaire as the information about DE, except age at inclusion, which was extracted from the National Registry of Norway. Age was further categorized into three groups; 46–55, 56–65 and 66–76 years old, respectively. Body mass index (BMI) was calculated from self-reported weight and height, and used in a continuous form. The validity of self-reported height and weight in NOWAC has been found satisfactory [24]. Education was categorized into three groups based on years of completed education, corresponding to secondary school (<10 years), high school (10–12 years) and higher education (>12 years). Employment status was categorized into three groups; employment (full-time or part-time), retired and unemployed. Marital status was included as a dichotomous variable as having a partner (married or domestic relationship) or not. Physical activity was measured on an ordinal scale from 1–10, and further categorized into groups of low (1–4), moderate (5–6) and high (≥7) physical activity. The self-reported physical activity in NOWAC has been found to be valid [25]. Alcohol intake measured in gram per day was included as a dichotomous variable indicating higher or lower consumption than the median intake. Total energy intake (kcal/day) was calculated from the comprehensive food frequency questionnaire and used as a dichotomous variable similar to alcohol intake. The NOWAC food frequency questionnaire has been validated against repeated 24h dietary recalls and found valid [26]. Smoking status was assembled in the categories; never, former and current. Self-rated health was assembled in three categories; very good, good or poor/very poor. The participants were asked whether they were ever diagnosed with depression by a doctor and this information was included as a dichotomous variable (yes/no) in the regression analysis.

Statistical analyses

Characteristics of women with DE were compared to women with no DE using independent t-test, Kruskal Wallis test and chi-square test, when appropriate. Multiple logistic regression analysis was used to identify the variables associated with DE and the strength of their relationships. The analyses were performed in accordance with the model building strategy for logistic regression described in Veierød et al [27]. Briefly, univariable analyses were used to explore the unadjusted associations between individual variables and DE as outcome. Variables with a significance level of p<0.25 were selected for inclusion in the multivariable analysis. Stepwise elimination of variables with p>0.05 was applied, and the full and the reduced models were compared using likelihood ratio tests. The percentage change of the regression coefficients between the full and reduced model was also assessed. If the regression coefficients changed by more than 20% after exclusion of a variable, that variable was re-entered into the model even if the likelihood ratio test suggested that it was not important for describing the odds of DE. The final model included only variables that were significantly associated with DE after mutual adjustments, or variables that confounded the effects of the other variables. Finally, we examined diagnostic plots of the residuals and tested the final model for overall goodness-of-fit using the Hosmer-Lemeshow test. Results are presented as crude and adjusted odds ratios (OR) including 95% confidence intervals (CI). Observations with any missing values on the included variables were excluded from the model. After cross-tabulations, we made an a priori decision not to test for interactions due to the lack of statistical power. All statistical analyses were conducted using the statistical software R version 3.4.3 and statistically significant results were defined as p-values <0.05.


Of the 90 592 women included in the present study, 253 reported DE by either selecting AN, BN or both in the questionnaires. This corresponds to an overall period prevalence of 0.28% (95% confidence interval 0.25–0.31%) during 2002–2005 among Norwegian women aged 46–76 years. The prevalence of DE in the oldest age group (≥ 66 years) was significantly higher (0.65% [95% confidence interval 0.60–0.70%]) than in the two younger age groups (Table 1).

Table 1. Total prevalence of disordered eating in 2002–2005 and stratified by age.

The Norwegian Women and Cancer Study (n = 90 592).

The 253 women with DE differed significantly (p <0.05) from the women without DE on several sociodemographic and lifestyle-related characteristics (Table 2). After mutual adjustments, DE was strongly associated with ever being diagnosed with depression (Odds Ratio [OR] 3.34 [95% confidence interval 2.53–4.41]), being unemployed (OR 1.78 [1.32–2.40]) and single (OR 1.66 [1.25–2.20]). In addition, women with DE were more likely to report a low energy intake (OR 1.41 [1.08–1.86]) and less likely to perform moderate physical activity (OR 0.67 [0.47–0.95]) than women without DE (Table 3). In the logistic regression analysis, 39 women with DE that had missing information on the investigated characteristics were excluded. Characteristics according to DE status in the sample with complete observations (n = 214, S1 Table) differed only slightly from the initial sample. Specifically, there was no significant difference in education level between women with and without DE in the sample with complete observations.

Table 2. Characteristics of women with and without disordered eating.

The Norwegian Women and Cancer Study (n = 90 592), 2002–2005.

Table 3. Logistic regression estimates for disordered eating in The Norwegian Women and Cancer Study 2002–2005.

Complete case analysis (n = 81 310, n case = 214). Reference group for the dependent variable was women with no disordered eating (n = 81 096).


In the present study of a representative sample of 90 592 women between 46 and 76 years of age from Norway, we estimated an overall period prevalence of 0.28 (95% confidence interval 0.25–0.31) % of DE during 2002–2005. This finding clearly supports the accumulating evidence that DE do occur also in women in mid-life and in older ages [7, 8, 2832]. Along with previous studies [10], our finding that the oldest age group (66–76 years) had the highest prevalence of DE contradict the notion that DE and eating disorder symptoms decline throughout the life span [12, 14].

The prevalence rate of 0.28% of DE in 2002–2005 suggest that DE is not a frequent problem among Norwegian women above 45 years. As the definition of DE is highly variable in previous literature, comparison of prevalence rates across studies are difficult. The perhaps closest comparison with respect to sample size and population is the study by Eik-Nes et al. [13] who reported a prevalence of DE of 12% in 2006–2008 among close to 25 000 Norwegian women between 30 and 99 years from mid-Norway. The huge discrepancy in prevalence compared to our findings is noteworthy, but may at least partly be explained by how DE was measured. For obvious reasons lower prevalence figures may be obtained by alluding to AN or BN than by using self-report questionnaires where eating patterns are scored and interpreted as DE indicators without necessarily being perceived as deviant by the respondents.

Depression was the strongest correlate of DE in the present study (Table 3). Women reporting DE had more than three-fold higher odds of ever being diagnosed with depression. Being unemployed and single were further associated with increased odds of DE. These findings suggest that DE and clinically significant eating disorders share common correlates as comorbid mood disorders [18, 33, 34], and impairment in role functioning at home, work or in social life [2, 11] have been reported in previous population-based studies of eating disorders. This argument is however, challenged as the correlation between increased alcohol intake and eating disorders [17, 35] was not observed in the present study (Tables 2 and 3 and S1 Table). The relationship between DE and physical activity in our study were U-shaped, where both low and high physical activity was associated with DE. High physical activity levels have been associated with AN in previous studies [36, 37]. Apart from a few studies [38, 39] indicating that low physical activity may be associated with recovery from AN in younger females, the relationship between AN and low physical activity is rather unknown.

Our results showed that DE and BMI were unrelated, which contrast other studies, e.g. Ng et al., 2013 [9]. This could be explained by the fact that the NOWAC questionnaire did not include a question about BED, where overweight is prevalent. Additionally, over- and underestimations of body weight among women with AN and/or BN may have caused measurement errors as people in general, as well as those having BN, tend to underestimate their weight and overestimate their height [40], while people with AN may overestimate their weight [41, 42] as a reflection of their fear of over-weight. This fear may also lead to an avoidance of any questions about their weight, indicated by the fact that the amount of missing information on BMI was slightly higher in the DE group (5.9%) as compared to the no DE group (3.8%) in our study. Similar findings of no difference in body weight between women with and without eating disorders have been reported in previous population-based studies among women aged 15–50 years [12, 43]. Additional analyses comparing the AN and the BN groups could have been relevant. However, as AN and BN cases were identified from only one question and many respondents ticked off both the AN and the BN option, such analyses were not considered. In addition, we did not have statistical power to assess AN or BN in stratified analyses.

Important strengths of this study are the large and nationally representative sample of Norwegian middle-aged women, and the comprehensive information about each woman’s lifestyle, and sociodemographic characteristics. Moreover, considering the large variations in how DE is operationalized in the literature, DE was more precisely defined as self-reported AN and/or BN. As the general population is fairly well informed about the features of AN and BN in the community [44], this operationalization may prevent overestimated prevalence figures of DE by capturing trivial problems within a normal variation, and with negligible psychological significance. Previous studies have suggested that the prevalence of AN and BN have been relatively stable in recent years among subjects above 40 years of age [45]. A similar trend has been observed in younger women as well [4547]. Thus, although our data was collected more than 10 years ago, the presented numbers are likely representative for the current situation among Norwegian middle-aged women. Our data can also serve as a benchmarking study for future studies of time-trends of DE among Norwegian women as the estimates are national representative. Moreover, the associations between DE and sociodemographic and lifestyle factors are not likely to be affected by the time of data collection.

The NOWAC study was not specifically designed for studying DE or its diagnostic counterparts. One may therefore have evaded the known underreport caused by people with DE or eating disorders in the population who do not sign up for a survey on DE [48] for reasons related to the (self)-stigmatization of suffering from DE and eating disorders [4953]. On the other hand, the present study cannot inform about the behavioral and cognitive aspects of DE or the prevalence of AN or BN determined by diagnostic screening tools for eating disorders [54]. The failure to include questions about BED is unfortunate given the high prevalence of BED symptoms, particularly in the older age cohorts of the general population [21, 29, 30, 32, 55]. Thus, the prevalence figures reported in the present study may be regarded as conservative estimates of the true population prevalence. In addition, the detection of possible correlates of DE was hampered by the low number (n = 214) of self-reported DE in the final regression model, and the cross-sectional design limited our ability to assess causality.

To conclude, the present study confirms previous smaller scaled studies in showing that DE do occur in mid-life and older age women. We have also identified factors associated with DE in this population. Our results contribute to address a somewhat under-communicated community health problem that needs attention in terms of age-specific treatment and prevention.

Supporting information

S1 Table. Characteristics of women with and without disordered eating included in the logistic regression analysis.

The Norwegian Women and Cancer Study (n = 81 310), 2002–2005.



We are thankful to the women that participated in the NOWAC research study. Bente Augdal and Merete Albertsen have been responsible for the administration of the data collection.


  1. 1. Slane JD, Klump KL, McGue M, Iacono WG. Developmental trajectories of disordered eating from early adolescence to young adulthood: a longitudinal study. Int J Eat Disord. 2014;47:793–801. pmid:24995824
  2. 2. Hudson JI, Hiripi E, Pope HG Jr., Kessler RC. The prevalence and correlates of eating disorders in the National Comorbidity Survey Replication. Biol Psychiatry. 2007;61:348–58. pmid:16815322
  3. 3. Harris M, Cumella EJ. Eating disorders across the life span. J Psychosoc Nurs Ment Health Serv. 2006;44:20–6.
  4. 4. Janelli LM. Body image in older adults: a review of the literature. Rehabil Nurs. 1986;11:6–8.
  5. 5. Lapid MI, Prom MC, Burton MC, McAlpine DE, Sutor B, Rummans TA. Eating disorders in the elderly. Int Psychogeriatr. 2010;22:523–36. pmid:20170590
  6. 6. Hsu LKG, Zimmer B. Eating disorders in old age. International Journal of Eating Disorders. 1988;7:133–8.
  7. 7. Gadalla TM. Eating disorders and associated psychiatric comorbidity in elderly Canadian women. Arch Womens Ment Health. 2008;11:357–62. pmid:18791783
  8. 8. Mangweth-Matzek B, Rupp CI, Hausmann A, Assmayr K, Mariacher E, Kemmler G, et al. Never too old for eating disorders or body dissatisfaction: a community study of elderly women. Int J Eat Disord. 2006;39:583–6. pmid:17078123
  9. 9. Ng IS, Cheung KC, Chou KL. Correlates of eating disorder in middle-aged and older adults: evidence from 2007 British National Psychiatric Morbidity Survey. J Aging Health. 2013;25:1106–20. pmid:23832843
  10. 10. Runfola CD, Von Holle A, Trace SE, Brownley KA, Hofmeier SM, Gagne DA, et al. Body dissatisfaction in women across the lifespan: results of the UNC-SELF and Gender and Body Image (GABI) studies. Eur Eat Disord Rev. 2013;21:52–9. pmid:22949165
  11. 11. Preti A, Girolamo G, Vilagut G, Alonso J, Graaf R, Bruffaerts R, et al. The epidemiology of eating disorders in six European countries: results of the ESEMeD-WMH project. J Psychiatr Res. 2009;43:1125–32. pmid:19427647
  12. 12. Gagne DA, Von Holle A, Brownley KA, Runfola CD, Hofmeier S, Branch KE, et al. Eating disorder symptoms and weight and shape concerns in a large web-based convenience sample of women ages 50 and above: results of the Gender and Body Image (GABI) study. Int J Eat Disord. 2012;45:832–44. pmid:22729743
  13. 13. Eik-Nes T, Romild U, Guzey I, Holmen T, Micali N, Bjornelv S. Women’s weight and disordered eating in a large Norwegian community sample: the Nord-Trondelag Health Study (HUNT). BMJ Open. 2015;5:e008125. pmid:26453589
  14. 14. Becker CB, Diedrichs PC, Jankowski G, Werchan C. I’m not just fat, I’m old: has the study of body image overlooked "old talk"? J Eat Disord. 2013;1:6. pmid:24764529
  15. 15. Beck D, Casper R, Andersen A. Truly late onset of eating disorders: a study of 11 cases averaging 60 years of age at presentation. Int J Eat Disord. 1996;20:389–95. pmid:8953326
  16. 16. Cederlof M, Thornton LM, Baker J, Lichtenstein P, Larsson H, Ruck C, et al. Etiological overlap between obsessive-compulsive disorder and anorexia nervosa: a longitudinal cohort, multigenerational family and twin study. World Psychiatry. 2015;14:333–8. pmid:26407789
  17. 17. Gadalla T, Piran N. Co-occurrence of eating disorders and alcohol use disorders in women: a meta analysis. Arch Womens Ment Health. 2007;10:133–40. pmid:17533558
  18. 18. Godart NT, Perdereau F, Rein Z, Berthoz S, Wallier J, Jeammet P, et al. Comorbidity studies of eating disorders and mood disorders. Critical review of the literature. J Affect Disord. 2007;97:37–49. pmid:16926052
  19. 19. Welch E, Jangmo A, Thornton LM, Norring C, von Hausswolff-Juhlin Y, Herman BK, et al. Treatment-seeking patients with binge-eating disorder in the Swedish national registers: clinical course and psychiatric comorbidity. BMC Psychiatry. 2016;16:163. pmid:27230675
  20. 20. Root TL, Pisetsky EM, Thornton L, Lichtenstein P, Pedersen NL, Bulik CM. Patterns of co-morbidity of eating disorders and substance use in Swedish females. Psychol Med. 2010;40:105–15. pmid:19379530
  21. 21. Rosenvinge JH, Pettersen G. Epidemiology of eating disorders part II: an update with a special reference to the DSM-5. Adv Eat Disord. 2015;3:198–220.
  22. 22. Lund E, Dumeaux V, Braaten T, Hjartaker A, Engeset D, Skeie G, et al. Cohort profile: The Norwegian women and cancer study—NOWAC—Kvinner og kreft. Int J Epidemiol. 2008;37:36–41. pmid:17644530
  23. 23. Lund E, Kumle M, Braaten T, Hjartåker A, Bakken K, Eggen E, et al. External validity in a population-based national prospective study—the Norwegian Women and Cancer Study (NOWAC). Cancer Causes Control. 2003;14:1001–8. pmid:14750540
  24. 24. Skeie G, Mode N, Henningsen M, Borch KB. Validity of self-reported body mass index among middle-aged participants in the Norwegian Women and Cancer study. Clin Epidemiol. 2015;7:313–23. pmid:26170718
  25. 25. Borch KB, Ekelund U, Brage S, Lund E. Criterion validity of a 10-category scale for ranking physical activity in Norwegian women. Int J Behav Nutr Phys Act. 2012;9:2. pmid:22260340
  26. 26. Hjartaker A, Andersen LF, Lund E. Comparison of diet measures from a food-frequency questionnaire with measures from repeated 24-hour dietary recalls. The Norwegian Women and Cancer Study. Public Health Nutr. 2007;10:1094–103. pmid:17381903
  27. 27. Veierod MB, Lydersen S, Laake P. Medical Statistics in clinical and epidemiological research. 1st ed. Oslo, Norway: Gyldendal Akademisk; 2012.
  28. 28. Conceicao EM, Gomes FVS, Vaz AR, Pinto-Bastos A, Machado PPP. Prevalence of eating disorders and picking/nibbling in elderly women. Int J Eat Disord. 2017;50:793–800. pmid:28301060
  29. 29. Hay P, Girosi F, Mond J. Prevalence and sociodemographic correlates of DSM-5 eating disorders in the Australian population. J Eat Disord. 2015;3:19. pmid:25914826
  30. 30. Mangweth-Matzek B, Hoek HW, Rupp CI, Lackner-Seifert K, Frey N, Whitworth AB, et al. Prevalence of eating disorders in middle-aged women. Int J Eat Disord. 2014;47:320–4. pmid:24293379
  31. 31. Micali N, Martini MG, Thomas JJ, Eddy KT, Kothari R, Russell E, et al. Lifetime and 12-month prevalence of eating disorders amongst women in mid-life: a population-based study of diagnoses and risk factors. BMC Med. 2017;15:12. pmid:28095833
  32. 32. Mitchison D, Hay PJ. The epidemiology of eating disorders: genetic, environmental, and societal factors. Clin Epidemiol. 2014;6:89–97. pmid:24728136
  33. 33. Gadalla T, Piran N. Psychiatric comorbidity in women with disordered eating behavior: a national study. Women Health. 2008;48:467–84. pmid:19301534
  34. 34. Swanson SA, Crow SJ, Le Grange D, Swendsen J, Merikangas KR. Prevalence and correlates of eating disorders in adolescents. Results from the national comorbidity survey replication adolescent supplement. Arch Gen Psychiatry. 2011;68:714–23. pmid:21383252
  35. 35. Fouladi F, Mitchell JE, Crosby RD, Engel SG, Crow S, Hill L, et al. Prevalence of Alcohol and Other Substance Use in Patients with Eating Disorders. Eur Eat Disord Rev. 2015;23:531–6. pmid:26415622
  36. 36. Bratland-Sanda S, Sundgot-Borgen J, Ro O, Rosenvinge JH, Hoffart A, Martinsen EW. "I’m not physically active—I only go for walks": physical activity in patients with longstanding eating disorders. Int J Eat Disord. 2010;43:88–92. pmid:19728373
  37. 37. El Ghoch M, Calugi S, Pellegrini M, Milanese C, Busacchi M, Battistini NC, et al. Measured physical activity in anorexia nervosa: features and treatment outcome. Int J Eat Disord. 2013;46:709–12. pmid:23712420
  38. 38. Hechler T, Rieger E, Touyz S, Beumont P, Plasqui G, Westerterp K. Physical activity and body composition in outpatients recovering from anorexia nervosa and healthy controls. Adapt Phys Activ Q. 2008;25:159–73. pmid:18493090
  39. 39. Seigel K, Hetta J. Exercise and eating disorder symptoms among young females. Eat Weight Disord. 2001;6:32–9. pmid:11300543
  40. 40. Connor Gorber S, Tremblay M, Moher D, Gorber B. A comparison of direct vs. self-report measures for assessing height, weight and body mass index: a systematic review. Obes Rev. 2007;8:307–26. pmid:17578381
  41. 41. McCabe RE, McFarlane T, Polivy J, Olmsted MP. Eating disorders, dieting, and the accuracy of self-reported weight. Int J Eat Disord. 2001;29:59–64. pmid:11135334
  42. 42. Meyer C, Arcelus J, Wright S. Accuracy of self-reported weight and height among women with eating disorders: a replication and extension study. Eur Eat Disord Rev. 2009;17:366–70. pmid:19618382
  43. 43. Ro O, Reas DL, Rosenvinge J. The impact of age and BMI on Eating Disorder Examination Questionnaire (EDE-Q) scores in a community sample. Eat Behav. 2012;13:158–61. pmid:22365803
  44. 44. Murray S, Touyz S, Beumont P. Knowledge about eating disorders in the community. Int J Eat Disord. 1990;9:87–93.
  45. 45. Steinhausen HC, Jensen CM. Time trends in lifetime incidence rates of first-time diagnosed anorexia nervosa and bulimia nervosa across 16 years in a Danish nationwide psychiatric registry study. Int J Eat Disord. 2015;48:845–50. pmid:25809026
  46. 46. Litmanen J, Frojd S, Marttunen M, Isomaa R, Kaltiala-Heino R. Are eating disorders and their symptoms increasing in prevalence among adolescent population? Nord J Psychiatry. 2017;71:61–6. pmid:27626363
  47. 47. Currin L, Schmidt U, Treasure J, Jick H. Time trends in eating disorder incidence. Br J Psychiatry. 2005;186:132–5. pmid:15684236
  48. 48. Fairburn CG, Wilson GT, Schleimer K. Binge eating: Nature, assessment, and treatment: Guilford Press New York; 1993.
  49. 49. Bannon KL, Hunter-Reel D, Wilson GT, Karlin RA. The effects of causal beliefs and binge eating on the stigmatization of obesity. Int J Eat Disord. 2009;42:118–24. pmid:18798228
  50. 50. Ebneter DS, Latner JD. Stigmatizing attitudes differ across mental health disorders: a comparison of stigma across eating disorders, obesity, and major depressive disorder. J Nerv Ment Dis. 2013;201:281–5. pmid:23538972
  51. 51. Pettersen G, Rosenvinge JH, Ytterhus B. The "double life" of bulimia: patients’ experiences in daily life interactions. Eat Disord. 2008;16:204–11. pmid:18443978
  52. 52. Roehrig JP, McLean CP. A comparison of stigma toward eating disorders versus depression. Int J Eat Disord. 2010;43:671–4. pmid:19816860
  53. 53. Stewart MC, Keel PK, Schiavo RS. Stigmatization of anorexia nervosa. Int J Eat Disord. 2006;39:320–5. pmid:16523470
  54. 54. Mond JM, Hay PJ, Rodgers B, Owen C, Beumont PJ. Validity of the Eating Disorder Examination Questionnaire (EDE-Q) in screening for eating disorders in community samples. Behav Res Ther. 2004;42:551–67. pmid:15033501
  55. 55. Hoek HW. Review of the worldwide epidemiology of eating disorders. Curr Opin Psychiatry. 2016;29:336–9. pmid:27608181