Eating disorder behaviours amongst adolescents: investigating classification, persistence and prospective associations with adverse outcomes using latent class models

European Child & Adolescent Psychiatry - Tập 26 - Trang 231-240 - 2016
Nadia Micali1,2,3, N. J. Horton4, R. D. Crosby5,6, S. A. Swanson7,8, K. R. Sonneville9, F. Solmi10, J. P. Calzo11, K. T. Eddy12,13, A. E. Field14
1Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, USA
2Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, USA
3Institute of Child Health, University College London, London, UK
4Department of Mathematics and Statistics, Amherst College, Amherst, USA
5Department of Biomedical Statistics, Neuropsychiatric Research Institute, Fargo, USA
6Department of Psychiatry and Behavioral Science, University of North Dakota School of Medicine and Health Sciences, Fargo, USA
7Department of Epidemiology, Harvard T. H. ChanSchool of Public Health, Boston, USA
8Department of Epidemiology, Erasmus MC, Rotterdam, Netherlands
9Human Nutrition Program, Department of Environmental Health Sciences, University of Michigan School of Public Health, Ann Arbor, USA
10Division of Psychiatry, University College London, London, UK
11Division of Adolescent Medicine, Department of Medicine, Boston Children’s Hospital and Harvard Medical School, Boston, USA
12Department of Psychiatry, Harvard Medical School, Boston, USA
13Eating Disorders Clinical and Research Program, Massachusetts General Hospital, Boston, USA
14Department of Epidemiology, Brown University School of Public Heath, Providence, USA

Tóm tắt

Diagnostic criteria for eating disorders (ED) remain largely based on clinical presentations, but do not capture the full range of behaviours in the population. We aimed to derive an empirically based ED behaviour classification using behavioural and body mass index (BMI) indicators at three time-points in adolescence, and to validate classes investigating prospective associations with adverse outcomes. Adolescents from the Avon Longitudinal Study of Parents and Children (ALSPAC) provided data on ED at age 14 (n = 6615), 16 (n = 5888), and 18 years (n = 5100), and had weight and height measured. Psychological and behavioural outcomes were assessed at 15.5/16 and 17.5/18 years. We fit gender- and age-stratified latent class models, and employed logistic regression to investigate associations between classes and later outcomes. One asymptomatic and two symptomatic (largely representing higher and lower frequency ED behaviours) classes were observed at each time-point, although their relative prevalence varied by age and gender. The majority of girls in symptomatic classes remained symptomatic at subsequent assessments. Girls in symptomatic classes had higher odds of subsequent anxiety and depressive disorders, binge drinking, drug use, and deliberate self-harm. Data analyses were underpowered amongst boys. The presence of two symptomatic classes (characterised by different ED behaviour frequency) and their prospective association with adverse outcomes suggest a need to refine diagnostic thresholds based on empirical data. Despite some instability of classes, particularly in mid-adolescence, evidence that half of girls in symptomatic classes remained symptomatic suggests persistence of ED behaviours in adolescence, and highlights a need for early identification to reduce chronicity.

Tài liệu tham khảo

Micali N, Hagberg KW, Petersen I, Treasure JL (2013) The incidence of eating disorders in the UK in 2000–2009: findings from the General Practice Research Database. BMJ Open. doi:10.1136/bmjopen-2013-002646 Field AE, Sonneville KR, Micali N, Crosby RD, Swanson SA, Laird NM, Treasure J, Solmi F, Horton NJ (2012) Prospective association of common eating disorders and adverse outcomes. Pediatrics 130(2):e289–e295. doi:10.1542/peds.2011-3663 Keshaviah A, Edkins K, Hastings ER, Krishna M, Franko DL, Herzog DB, Thomas JJ, Murray HB, Eddy KT (2014) Re-examining premature mortality in anorexia nervosa: a meta-analysis redux. Compr Psychiatry 55(8):1773–1784. doi:10.1016/j.comppsych.2014.07.017 Micali N, Solmi F, Horton NJ, Crosby RD, Eddy KT, Calzo JP, Sonneville KR, Swanson SA, Field AE (2015) Adolescent Eating Disorders Predict Psychiatric, High-Risk Behaviors and Weight Outcomes in Young Adulthood. J Am Acad Child Adolesc Psychiatry 54 (8):652-659.e651. doi:10.1016/j.jaac.2015.05.009 American Psychiatric A (2013) Diagnostic and Statistical Manual of Mental Disorders, 5th edn. Arlington, VA Organization WH ICD-11 Beta Draft. http://apps.who.int/classifications/icd11/browse/l-m/en#/http%3a%2f%2fid.who.int%2ficd%2fentity%2f263852475. Accessed October 2015 Wonderlich SA, Joiner TE Jr, Keel PK, Williamson DA, Crosby RD (2007) Eating disorder diagnoses: empirical approaches to classification. Am Psychol 62(3):167–180. doi:10.1037/0003-066x.62.3.167 Feinstein AR (1972) Clinical biostatistics. 13. On homogeneity, taxonomy, and nosography. Clin Pharmacol Ther 13(1):114–129 Eddy KT, Swanson SA, Crosby RD, Franko DL, Engel S, Herzog DB (2010) How should DSM-V classify eating disorder not otherwise specified (EDNOS) presentations in women with lifetime anorexia or bulimia nervosa? Psychol Med 40(10):1735–1744. doi:10.1017/s0033291709992200 Eddy KT, Celio Doyle A, Hoste RR, Herzog DB, le Grange D (2008) Eating disorder not otherwise specified in adolescents. J Am Acad Child Adolesc Psychiat 47(2):156–164. doi:10.1097/chi.0b013e31815cd9cf Swanson SA, Crow SJ, Le Grange D, Swendsen J, Merikangas KR (2011) Prevalence and correlates of eating disorders in adolescents. Results from the national comorbidity survey replication adolescent supplement. Arch Gen Psychiat 68(7):714–723. doi:10.1001/archgenpsychiatry.2011.22 Solmi F, Hotopf M, Hatch S, Treasure J, Micali N (2015) Eating disorders in a multi-ethnic inner-city UK sample: prevalence, comorbidity and service use. Social Psychiatry and Psychiatric Epidemiology Dec 2 Epub ahead of print Waller G, Micali N, James A (2014) General Practitioners are poor at identifying the eating disorders. Adv Eat Disord 2(2):146–157 Klein JD, Wilson KM, McNulty M, Kapphahn C, Collins KS (1999) Access to medical care for adolescents: results from the 1997 Commonwealth Fund Survey of the Health of Adolescent Girls. J Adolesc Health 25(2):120–130 Davey A, Carter M, Campbell JL (2013) Priorities for young adults when accessing UK primary care: literature review. Primary Health Care Res Dev 14(4):341–349. doi:10.1017/s1463423612000497 Kansi J, Wichstrøm L, Bergman L (2005) Eating problems and their risk factors: a 7-year longitudinal study of a population sample of norwegian adolescent girls. J Youth Adolesc 34(6):521–531. doi:10.1007/s10964-005-8935-3 Cain AS, Epler AJ, Steinley D, Sher KJ (2010) Stability and change in patterns of concerns related to eating, weight, and shape in young adult women: a latent transition analysis. J Abnorm Psychol 119(2):255–267. doi:10.1037/a0018117 Swanson SA, Horton NJ, Crosby RD, Micali N, Sonneville KR, Eddy K, Field AE (2014) A latent class analysis to empirically describe eating disorders through developmental stages. Int J Eat Disord 47(7):762–772. doi:10.1002/eat.22308 Micali N, Ploubidis G, De Stavola B, Simonoff E, Treasure J (2014) Frequency and patterns of eating disorder symptoms in early adolescence. J Adolesc Health 54(5):574–581. doi:10.1016/j.jadohealth.2013.10.200 Boyd A, Golding J, Macleod J, Lawlor DA, Fraser A, Henderson J, Molloy L, Ness A, Ring S, Smith GD (2013) Cohort Profile: The ‘Children of the 90 s’—the index offspring of the Avon Longitudinal Study of Parents and Children. Int J Epidemiol 42(1):111–127 Golding J, Pembrey M, Jones R (2001) ALSPAC–the Avon Longitudinal Study of Parents and Children. I. Study methodology. Paediatr Perinat Epidemiol 15(1):74–87 Kann L, Warren CW, Harris WA, Collins JL, Williams BI, Ross JG (1995) Kolbe LJ (1996) Youth risk behavior surveillance—United States. J Sch Health 66(10):365–377 Micali N, De Stavola B, Ploubidis G, Simonoff E, Treasure J, Field AE (2015) Adolescent eating disorder behaviours and cognitions: gender-specific effects of child, maternal and family risk factors. Br J Psychiatry 207(4):320–327. doi:10.1192/bjp.bp.114.152371 Field AE, Taylor CB, Celio A, Colditz GA (2004) Comparison of self-report to interview assessment of bulimic behaviors among preadolescent and adolescent girls and boys. Int J Eat Disord 35(1):86–92 StataCorp (2011) Stata Statistical Software: Release 12. Stata Corp LP, College Station, TX Cole TJ, Bellizzi MC, Flegal KM, Dietz WH (2000) Establishing a standard definition for child overweight and obesity worldwide: international survey. BMJ 320(7244):1240–1243 Goodman R, Ford T, Richards H, Gatward R, Meltzer H (2000) The Development and Well-Being Assessment: description and initial validation of an integrated assessment of child and adolescent psychopathology. JChild PsycholPsychiatry 41(5):645–655 Lewis G, Pelosi AJ, Araya R, Dunn G (1992) Measuring psychiatric disorder in the community: a standardized assessment for use by lay interviewers. Psychol Med 22(2):465–486 Messer SC, Angold A, Costello EJ, Loeber R, VanKammen W, StouthamerLoeber M (1995) Development of a short questionnaire for use in epidemiological studies of depression in children and adolescents: Factor composition and structure across development. Int J Meth Psychiat Res 5:251–262 Sharp C, Goodyer IM, Croudace TJ (2006) The Short Mood and Feelings Questionnaire (SMFQ): a unidimensional item response theory and categorical data factor analysis of self-report ratings from a community sample of 7-through 11-year-old children. J Abnorm Child Psychol 34(3):379–391 Kuo ES, Stoep AV, Stewart DG (2005) Using the short mood and feelings questionnaire to detect depression in detained adolescents. Assessment 12(4):374–383 Bohn MJ, Babor TF, Kranzler HR (1995) The Alcohol Use Disorders Identification Test (AUDIT): validation of a screening instrument for use in medical settings. J Stud Alcohol 56(4):423–432 Goodman A, Heiervang E, Collishaw S, Goodman R (2011) The ‘DAWBA bands’ as an ordered-categorical measure of child mental health: description and validation in British and Norwegian samples. Soc Psychiatry Psychiatr Epidemiol 46(6):521–532. doi:10.1007/s00127-010-0219-x Little RJ, Rubin DB (2002) Statistical analysis with missing data, 2nd edn. Wiley, New York Swanson SA, Lindenberg K, Bauer S, Crosby RD (2012) A Monte Carlo investigation of factors influencing latent class analysis: an application to eating disorder research. Int J Eat Disord 45(5):677–684. doi:10.1002/eat.20958 Duncan AE, Bucholz KK, Neuman RJ, Agrawal A, Madden PA, Heath AC (2007) Clustering of eating disorder symptoms in a general population female twin sample: a latent class analysis. Psychol Med 37(8):1097–1107. doi:10.1017/s0033291707000505 Eddy KT, Crosby RD, Keel PK, Wonderlich SA, le Grange D, Hill L, Powers P, Mitchell JE (2009) Empirical identification and validation of eating disorder phenotypes in a multisite clinical sample. J Nerv Ment Dis 197(1):41–49. doi:10.1097/NMD.0b013e3181927389 Calzo J, Horton N, Sonneville K, Swanson S, Crosby R, Micali N, Eddy K, Field A (2016) Male eating disorder symptom patterns and health correlates from ages 13 to 26 years of age. J Am Acad Child Adolesc Psychiatry. doi:10.1016/j.jaac.2016.05.011 Micali N, Hebebrand J (2015) Anorexia nervosa through the looking glass of the draft ICD-11 diagnostic criteria: a disorder in transition. Eur Child Adolesc Psychiatry 24(10):1149–1152. doi:10.1007/s00787-015-0771-8