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Childhood cognition and lifetime risk of major depressive disorder in extremely low birth weight and normal birth weight adults

Published online by Cambridge University Press:  25 July 2016

K. G. Dobson*
Affiliation:
Department of Clinical Epidemiology & Biostatistics, McMaster University, Hamilton, Ontario, Canada
L. A. Schmidt
Affiliation:
Department of Psychology, Neuroscience, and Behaviour, McMaster University, Hamilton, Ontario, Canada
S. Saigal
Affiliation:
Department of Paediatrics, McMaster University, Hamilton, Ontario, Canada
M. H. Boyle
Affiliation:
Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, Ontario, Canada
R. J. Van Lieshout
Affiliation:
Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, Ontario, Canada
*
*Address for correspondence: K. G. Dobson, Women’s Health Concerns Clinic, St. Joseph’s Hospital Hamilton, West 5th Campus, Room C142, 100 West 5th Street, Hamilton, ON L8N 3K7, Canada. (Email dobsonkg@mcmaster.ca)

Abstract

In general population samples, better childhood cognitive functioning is associated with decreased risk of depression in adulthood. However, this link has not been examined in extremely low birth weight survivors (ELBW, <1000 g), a group known to have poorer cognition and greater depression risk. This study assessed associations between cognition at age 8 and lifetime risk of major depressive disorder in 84 ELBW survivors and 90 normal birth weight (NBW, ⩾2500 g) individuals up to 29–36 years of age. The Wechsler Intelligence Scale for Children, Revised (WISC-R), Raven’s Coloured Progressive Matrices and the Token Test assessed general, fluid, and verbal intelligence, respectively, at 8 years of age. Lifetime major depressive disorder was assessed using the Mini International Neuropsychiatric Interview at age 29–36 years. Associations were examined using logistic regression adjusted for childhood socioeconomic status, educational attainment, age, sex, and marital status. Neither overall intelligence quotient (IQ) [WISC-R Full-Scale IQ, odds ratios (OR)=0.87, 95% confidence interval (CI)=0.43–1.77], fluid intelligence (WISC-R Performance IQ, OR=0.98, 95% CI=0.48–2.00), nor verbal intelligence (WISC-R Verbal IQ, OR=0.81, 95% CI=0.40–1.63) predicted lifetime major depression in ELBW survivors. However, every standard deviation increase in WISC-R Full-Scale IQ (OR=0.43, 95% CI=0.20–0.92) and Performance IQ (OR=0.46, 95% CI=0.21–0.97), and each one point increase on the Token Test (OR=0.80, 95% CI=0.67–0.94) at age 8 was associated with a reduced risk of lifetime depression in NBW participants. Higher childhood IQ, better fluid intelligence, and greater verbal comprehension in childhood predicted reduced depression risk in NBW adults. Our findings suggest that ELBW survivors may be less protected by superior cognition than NBW individuals.

Type
Original Article
Copyright
© Cambridge University Press and the International Society for Developmental Origins of Health and Disease 2016 

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References

1. Ferrari, AJ, Somerville, AJ, Baxter, AJ, et al. Global variation in the prevalence and incidence of major depressive disorder: a systematic review of the epidemiological literature. Psychol Med. 2013; 43, 471481.CrossRefGoogle ScholarPubMed
2. Ferrari, AJ, Charlson, FJ, Norman, RE, et al. Burden of depressive disorders by country, sex, age, and year: findings from the Global Burden of Disease Study 2010. PLoS Med. 2013; 10, e1001547.CrossRefGoogle ScholarPubMed
3. Ferrari, AJ, Charlson, FJ, Norman, RE, et al. The epidemiological modelling of major depressive disorder: application for the Global Burden of Disease Study 2010. PLoS One. 2013; 8, e69637.CrossRefGoogle ScholarPubMed
4. Whiteford, HA, Degenhardt, L, Rehm, J, et al. Global burden of disease attributable to mental and substance use disorders: findings from the Global Burden of Disease Study 2010. Lancet . 2013; 382, 15751586.CrossRefGoogle ScholarPubMed
5. Bloom, DE, Cafiero, ET, Jané-Llopis, E, et al. The Global Economic Burden of Noncommunicable Diseases. 2011; pp. 146. World Economic Forum: Geneva.Google Scholar
6. Andrade, L, Caraveo-Anduaga, JJ, Berglund, P, et al. The epidemiology of major depressive episodes: results from the International Consortium of Psychiatric Epidemiology (ICPE) Surveys. Int J Methods Psychiatr Res. 2003; 12, 321.CrossRefGoogle Scholar
7. Kessler, RC, Berglund, P, Demler, O, et al. The epidemiology of major depressive disorder: results from the National Comorbidity Survey Replication (NCS-R). JAMA. 2003; 289, 30953105.CrossRefGoogle ScholarPubMed
8. Barnett, JH, McDougall, F, Xu, MK, et al. Childhood cognitive function and adult psychopathology: associations with psychotic and non-psychotic symptoms in the general population. Br J Psychiatry. 2012; 201, 124130.CrossRefGoogle ScholarPubMed
9. Kremen, WS, Buka, SL, Seidman, LJ, et al. IQ decline during childhood and adult psychotic symptoms in a community sample: a 19-year longitudinal study. Am J Psychiatry. 1998; 155, 672677.CrossRefGoogle Scholar
10. Koenen, KC, Moffitt, TE, Roberts, AL, et al. Childhood IQ and adult mental disorders: a test of the cognitive reserve hypothesis. Am J Psychiatry. 2009; 166, 5057.CrossRefGoogle ScholarPubMed
11. Deary, IJ, Batty, GD. Cognitive epidemiology. J Epidemiol Community Health. 2007; 61, 378384.CrossRefGoogle ScholarPubMed
12. Hatch, SL, Jones, PB, Kuh, D, et al. Childhood cognitive ability and adult mental health in the British 1946 Birth Cohort. Soc Sci Med. 2007; 64, 22852296.CrossRefGoogle ScholarPubMed
13. Batty, GD, Mortensen, EL, Osler, M. Childhood intelligence in relation to later psychiatric disorder: evidence from a Danish birth cohort study. Br J Psychiatry. 2005; 187, 180181.CrossRefGoogle ScholarPubMed
14. Zammit, S, Allebeck, P, David, AS, et al. A longitudinal study of premorbid IQ score and risk of developing schizophrenia, bipolar disorder, severe depression, and other nonaffective psychoses. Arch Gen Psychiatry. 2004; 61, 354360.CrossRefGoogle ScholarPubMed
15. Stern, Y. The concept of cognitive reserve: a catalyst for research. J Clin Exp Neuropsychol. 2003; 25, 589593.CrossRefGoogle ScholarPubMed
16. Aylward, GP. Cognitive and neuropsychological outcomes: more than IQ scores. Ment Retard Dev Disabil Res Rev. 2002; 8, 234240.CrossRefGoogle ScholarPubMed
17. Margolis, A, Bansal, R, Hao, X, et al. Using IQ discrepancy scores to examine the neural correlates of specific cognitive abilities. J Neurosci. 2013; 33, 1413514145.CrossRefGoogle ScholarPubMed
18. Wolke, D, Strauss, VY, Johnson, S, et al. Universal gestational age effects on cognitive and basic mathematic processing: 2 cohorts in 2 countries. J Pediatr. 2015; 166, 14101416.e1–e2.CrossRefGoogle ScholarPubMed
19. Van Lieshout, RJ, Boyle, MH, Saigal, S, Morrison, K, Schmidt, LA. Mental health of extremely low birth weight survivors in their 30s. Pediatrics. 2015; 135, 452459.CrossRefGoogle ScholarPubMed
20. Baron, IS, Rey-Casserly, C. Extremely preterm birth outcome: a review of four decades of cognitive research. Neuropsychol Rev. 2010; 20, 430452.CrossRefGoogle ScholarPubMed
21. Bhutta, AT, Cleves, MA, Casey, PH, Cradock, MM, Anand, KJS. Cognitive and behavioral outcomes of school-aged children who were born preterm. JAMA. 2002; 288, 728737.CrossRefGoogle ScholarPubMed
22. Johnson, S, Hennessy, E, Smith, R, et al. Academic attainment and special educational needs in extremely preterm children at 11 years of age: the EPICure study. Arch Dis Child Fetal Neonatal Ed. 2009; 94, F283F289.CrossRefGoogle ScholarPubMed
23. Saigal, S, Szatmari, P, Rosenbaum, P, Campbell, D, King, S. Cognitive abilities and school performance of extremely low birth weight children and matched term control children at age 8 years: a regional study. J Pediatr. 1991; 118, 751760.CrossRefGoogle Scholar
24. Wechsler, D. Manual for the Wechsler Intelligence Scale for Children, Revised, 1974. Psychological Corporation: New York.Google Scholar
25. Raven, J. The Raven’s progressive matrices: change and stability over culture and time. Cogn Psychol. 2000; 41, 148.CrossRefGoogle ScholarPubMed
26. Raven, JC. Manual for the Coloured Progressive Matrices (Revised). 1984. NFER-Nelson: Windsor.Google Scholar
27. DiSimoni, F. The Token Test for Children, 1978. DLM Teaching Resources: Allen.Google Scholar
28. Sheehan, DV, Lecrubier, Y, Sheehan, KH, et al. The Mini-International Neuropsychiatric Interview (M.I.N.I.): the development and validation of a structured diagnostic psychiatric interview for DSM-IV and ICD-10. J Clin Psychiatry. 1998; 59(Suppl. 20), 2233.Google ScholarPubMed
29. Thompson, C, Syddall, H, Rodin, I, et al. Birth weight and the risk of depressive disorder in late life. Br J Psychiatry. 2001; 179, 450455.CrossRefGoogle ScholarPubMed
30. Paradiso, S, Hermann, BP, Blumer, D, Davies, K, Robinson, RG. Impact of depressed mood on neuropsychological status in temporal lobe epilepsy. J Neurol Neurosurg Psychiatry. 2001; 70, 180185.CrossRefGoogle ScholarPubMed
31. World Federation For Mental Health. Depression: a global crisis. World Health Organization [Internet]. 2012. Retrieved 1 August 2015 from http://www.who.int/mental_health/management/depression/wfmh_paper_depression_wmhd_2012.pdf.Google Scholar
32. McDermott, LM, Ebmeier, KP. A meta-analysis of depression severity and cognitive function. J Affect Disord. 2009; 119, 18.CrossRefGoogle ScholarPubMed
33. Haeffel, GJ, Grigorenko, EL. Cognitive vulnerability to depression: exploring risk and resilience. Child Adolesc Psychiatr Clin N Am. 2007; 16, 435448.CrossRefGoogle ScholarPubMed
34. Ressler, KJ, Mayberg, HS. Targeting abnormal neural circuits in mood and anxiety disorders: from the laboratory to the clinic. Nat Neurosci. 2007; 10, 11161124.CrossRefGoogle ScholarPubMed
35. Volpe, JJ. Brain injury in premature infants: a complex amalgam of destructive and developmental disturbances. Lancet Neurol. 2009; 8, 110124.CrossRefGoogle ScholarPubMed
36. Colman, I, Ataullahjan, A, Naicker, K, Van Lieshout, RJ. Birth weight, stress, and symptoms of depression in adolescence: evidence of fetal programming in a National Canadian Cohort. Can J Psychiatry. 2012; 57, 422428.CrossRefGoogle Scholar
37. Pyhälä, R, Räikkönen, K, Pesonen, AK, et al. Parental bonding after preterm birth: child and parent perspectives in the Helsinki study of very low birth weight adults. J Pediatr. 2011; 158, 251256.e1.CrossRefGoogle ScholarPubMed
38. Doyle, LW, Anderson, PJ. Adult outcome of extremely preterm infants. Pediatrics. 2010; 126, 342351.CrossRefGoogle ScholarPubMed
39. Wilkinson, PO, Goodyer, IM. Childhood adversity and allostatic overload of the hypothalamic–pituitary–adrenal axis: a vulnerability model for depressive disorders. Dev Psychopathol. 2011; 23, 10171037.CrossRefGoogle Scholar