Hostname: page-component-5d59c44645-hb754 Total loading time: 0 Render date: 2024-02-27T05:05:48.965Z Has data issue: false hasContentIssue false

What life course theoretical models best explain the relationship between exposure to childhood adversity and psychopathology symptoms: recency, accumulation, or sensitive periods?

Published online by Cambridge University Press:  26 February 2018

Erin C. Dunn*
Affiliation:
Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA Department of Psychiatry, Harvard Medical School, Boston, MA, USA Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
Thomas W. Soare
Affiliation:
Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA Department of Psychiatry, Harvard Medical School, Boston, MA, USA Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
Miriam R. Raffeld
Affiliation:
Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
Daniel S. Busso
Affiliation:
Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA Harvard Graduate School of Education, Cambridge, MA, USA
Katherine M. Crawford
Affiliation:
Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
Kathryn A. Davis
Affiliation:
Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
Virginia A. Fisher
Affiliation:
Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
Natalie Slopen
Affiliation:
Department of Epidemiology and Biostatistics, School of Public Health, University of Maryland, College Park, MD, USA
Andrew D.A.C. Smith
Affiliation:
Applied Statistics Group, University of the West of England, Bristol, UK
Henning Tiemeier
Affiliation:
Erasmus Medical Center, Rotterdam, The Netherlands
Ezra S. Susser
Affiliation:
Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, USA New York State Psychiatric Institute, New York, NY, USA
*
Author for correspondence: Erin C. Dunn, E-mail: edunn2@mgh.Harvard.edu, Website: www.thedunnlab.com

Abstract

Background

Although childhood adversity is a potent determinant of psychopathology, relatively little is known about how the characteristics of adversity exposure, including its developmental timing or duration, influence subsequent mental health outcomes. This study compared three models from life course theory (recency, accumulation, sensitive period) to determine which one(s) best explained this relationship.

Methods

Prospective data came from the Avon Longitudinal Study of Parents and Children (n = 7476). Four adversities commonly linked to psychopathology (caregiver physical/emotional abuse; sexual/physical abuse; financial stress; parent legal problems) were measured repeatedly from birth to age 8. Using a statistical modeling approach grounded in least angle regression, we determined the theoretical model(s) explaining the most variability (r2) in psychopathology symptoms measured at age 8 using the Strengths and Difficulties Questionnaire and evaluated the magnitude of each association.

Results

Recency was the best fitting theoretical model for the effect of physical/sexual abuse (girls r2 = 2.35%; boys r2 = 1.68%). Both recency (girls r2 = 1.55%) and accumulation (boys r2 = 1.71%) were the best fitting models for caregiver physical/emotional abuse. Sensitive period models were chosen alone (parent legal problems in boys r2 = 0.29%) and with accumulation (financial stress in girls r2 = 3.08%) more rarely. Substantial effect sizes were observed (standardized mean differences = 0.22–1.18).

Conclusions

Child psychopathology symptoms are primarily explained by recency and accumulation models. Evidence for sensitive periods did not emerge strongly in these data. These findings underscore the need to measure the characteristics of adversity, which can aid in understanding disease mechanisms and determining how best to reduce the consequences of exposure to adversity.

Type
Original Articles
Copyright
Copyright © Cambridge University Press 2018 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Andersen, SL, Tomada, A, Vincow, ES, Valente, E, Polcari, A and Teicher, MH (2008) Preliminary evidence for sensitive periods in the effect of childhood sexual abuse on regional brain development. The Journal of Neuropsychiatry & Clinical Neurosciences 20, 292301.Google Scholar
Bailey, DB, Bruer, JT, Symons, FJ and Lichtman, JW (eds.) (2001) Critical Thinking About Critical Periods. Baltimore, MD: Paul H. Brookes Publishing Company.Google Scholar
Ben-Shlomo, Y and Kuh, D (2002) A life course approach to chronic disease epidemiology: conceptual models, empirical challenges, and interdisciplinary perspectives. International Journal of Epidemiology 31, 285293.Google Scholar
Boyd, A, Golding, J, Macleod, J, Lawlor, DA, Fraser, A, Henderson, J et al. (2013) Cohort profile: the ‘children of the 90's’ – the index offspring of the Avon Longitudinal Study of Parents and Children. International Journal of Epidemiology 42, 111127.Google Scholar
Chilcoat, HD and Breslau, N (1997) Does psychiatric history bias mothers’ reports? An application of a new analytic approach. Journal of the American Academy of Child and Adolescent Psychiatry 36, 971979.Google Scholar
Cox, JL, Holden, JM and Sagovsky, R (1987) Detection of postnatal depression. Development of the 10-item Edinburgh Postnatal Depression Scale. The British Journal of Psychiatry 150, 782786.Google Scholar
Dong, M, Anda, RF, Felitti, VJ, Williamson, DF, Dube, SR, Brown, DW et al. (2005) Childhood residential mobility and multiple health risks during adolescence and adulthood: the hidden role of adverse childhood experiences. Archives of Pediatrics & Adolescent Medicine 159, 11041110.Google Scholar
Dunn, EC, Gilman, SE, Willett, JB, Slopen, N and Molnar, BE (2012) The impact of exposure to interpersonal violence on gender differences in adolescent-onset major depression: results from the National Comorbidity Survey Replication (NCS-R). Depression and Anxiety 29, 392399.Google Scholar
Dunn, EC, McLaughlin, KA, Slopen, N, Rosand, J and Smoller, JW (2013) Developmental timing of child maltreatment and symptoms of depression and suicidal ideation in young adulthood: results from the National Longitudinal Study of Adolescent Health. Depression and Anxiety 30, 955964.Google Scholar
Dunn, EC, Nishimi, K, Powers, A and Bradley, B (2016) Is developmental timing of trauma exposure associated with depressive and post-traumatic stress disorder symptoms in adulthood? Journal of Psychiatric Research 84, 119127.Google Scholar
Efron, B, Hastie, T, Johnstone, I and Tibshirani, R (2004) Least angle regression. The Annals of Statistics 32, 407499.Google Scholar
English, DJ, Graham, JC, Litrownik, AJ, Everson, M and Bangdiwala, SI (2005) Defining maltreatment chronicity: are there differences in child outcomes? Child Abuse & Neglect 29, 575595.Google Scholar
Evans, GW (2004) The environment of childhood poverty. American Psychologist 59, 7792.Google Scholar
Evans, GW, Li, D and Whipple, SS (2013) Cumulative risk and child development. Psychological Bulletin 139, 342396.Google Scholar
Ezpeleta, L, Granero, R, De La Osa, N, Penelo, E and Domènech, JM (2013) Psychometric properties of the strengths and difficulties questionnaire 3–4 in 3-year-old preschoolers. Comprehensive Psychiatry 54, 282291.Google Scholar
Felitti, VJ, Anda, RF, Nordenberg, D, Williamson, DF, Spitz, AM, Edwards, VJ et al. (1998) Relationships of childhood abuse and household dysfunction to many of the leading causes of death in adults: the adverse childhood experiences (ACE) study. American Journal of Preventive Medicine 14, 245258.Google Scholar
Gilbert, R, Spatz Widom, C, Browne, K, Fergusson, D, Webb, E and Janson, S (2009) Child maltreatment 1: burden and consequences of child maltreatment in high-income countries. The Lancet 373, 6881.Google Scholar
Gilman, SE, Ni, MY, Dunn, EC, Breslau, J, McLaughlin, KA, Smoller, JW et al. (2015) Contributions of the social environment to first-onset and recurrent mania. Molecular Psychiatry 20, 329336.Google Scholar
Goodman, A and Goodman, R (2011) Population mean scores predict child mental disorder rates: validating SDQ prevalence estimators in Britain. Journal of Child Psychology and Psychiatry 52, 100108.Google Scholar
Goodman, A, Lamping, DL and Ploubidis, GB (2010) When to use broader internalizing and externalizing subscales instead of the hypothesized five subscales on the strengths and difficulties questionnaire (SDQ); data from British parents, teachers, and children. Journal of Abnormal Child Psychology 38, 11791191.Google Scholar
Goodman, R (1997) The strengthts and difficulties questionnaire: a research note. Journal of Child Psychology and Psychiatry 38, 581586.Google Scholar
Goodman, R (2001) Psychometric properties of the strengthts and difficulties questionnaire. Journal of the American Academy of Child and Adolescent Psychiatry 40, 13371345.Google Scholar
Green, JG, McLaughlin, KA, Berglund, PA, Gruber, MJ, Sampson, NA, Zaslvasky, AM et al. (2010) Childhood adversities and adult psychiatric disorders in the National Comorbidity Survey Replication I: associations with first onset of DSM-IV disorders. Archives of General Psychiatry 67, 113123.Google Scholar
Harpur, LJ, Polek, E and Van Harmelen, AL (2015) The role of timing of maltreatment and child intelligence in pathways to low symptoms of depression and anxiety in adolescence. Child Abuse & Neglect 47, 2437.Google Scholar
Hibbeln, JR, Davis, JM, Steer, C, Emmett, P, Rogers, I, Williams, C et al. (2007) Maternal seafood consumption in pregnancy and neurodevelopmental outcomes in childhood (ALSPAC study): an observational cohort study. The Lancet 369, 578585.Google Scholar
Holmes, A, Le Guisquet, AM, Vogel, E, Millstein, RA, Leman, S and Belzung, C (2005) Early life genetic, epigenetic, and environmental factors shaping emotionality in rodents. Neuroscience and Biobehavioral Reviews 29, 13351346.Google Scholar
Holt, S, Buckley, H and Whelan, S (2008) The impact of exposure to domestic violence on children and young people: a review of the literature. Child Abuse & Neglect 32, 797810.Google Scholar
Jaffee, SR and Maikovich-Fong, AK (2011) Effects of chronic maltreatment and maltreatment timing on children's behavior and cognitive abilities. Journal of Child Psychology and Psychiatry 52, 184194.Google Scholar
Kaplow, JB and Widom, CS (2007) Age of onset of child maltreatment predicts long-term mental health outcomes. Journal of Abnormal Psychology 116, 176187.Google Scholar
Keiley, MK, Howe, TR, Dodge, KA, Bates, JE and Pettit, GS (2001) The timing of child physical maltreatment: a cross-domain growth analysis of impact on adolescent externalizing and internalizing problems. Development and Psychopathology 13, 891912.Google Scholar
Kendler, KS, Karkowski, LM and Prescott, CA (1999) Causal relationship between stressful life events and the onset of major depression. The American Journal of Psychiatry 156, 837841.Google Scholar
Knudsen, E (2004) Sensitive periods in the development of the brain and behavior. Journal of Cognitive Neuroscience 16, 14121425.Google Scholar
Koenen, KC, Roberts, A, Stone, D and Dunn, EC (2010) The epidemiology of early childhood trauma. In Lanius, R and Vermetten, E (eds) The Hidden Epidemic: The Impact of Early Life Trauma on Health and Disease. New York, NY: Oxford University, pp. 1324.Google Scholar
Kuh, D and Ben-Shlomo, Y (eds) (2004) A Life Course Approach to Chronic Disease Epidemiology. Oxford: Oxford University Press.Google Scholar
Liu, J, Dietz, K, Deloyht, JM, Pedre, X, Kelkar, D, Kaur, J et al. (2012) Impaired adult myelination in the prefrontal cortex of socially isolated mice. Nature Neuroscience 15, 16211623.Google Scholar
Lockhart, R, Taylor, J, Tibshirani, RJ and Tibshirani, R (2014) A significance test for the LASSO. Annals of Statistics 42, 413468.Google Scholar
Makinodan, M, Rosen, KM, Ito, S and Corfas, G (2012) A critical period for social experience-dependent oligodendrocyte maturation and myelination. Science 337, 13571360.Google Scholar
Maniglio, R (2009) The impact of child sexual abuse on health: a systematic review of reviews. Clinical Psychology Review 29, 647657.Google Scholar
Manly, JT, Kim, JE, Rogosch, FA and Cicchetti, D (2001) Dimensions of child maltreatment and children's adjustment: contributions of developmental timing and subtype. Development and Psychopathology 13, 759782.Google Scholar
McLaughlin, KA, Green, JG, Gruber, MJ, Sampson, NA, Zaslavsky, AM and Kessler, RC (2010) Childhood adversities and adult psychiatric disorders in the National Comorbidity Survey Replication II: associations with persistence of DSM-IV disorders. Archives of General Psychiatry 67, 124132.Google Scholar
McLaughlin, KA, Green, JG, Gruber, MJ, Sampson, NA, Zaslavsky, AM and Kessler, RC (2012) Childhood adversities and first onset of psychiatric disorders in a national sample of US adolescents. JAMA Psychiatry 69, 11511160.Google Scholar
McLaughlin, KA and Sheridan, MA (2016) Beyond cumulative risk: a dimensional approach to childhood adversity. Current Directions in Psychological Science 25, 239245.Google Scholar
Mishra, G, Nitsch, D, Black, S, De Stavola, B, Kuh, D and Hardy, R (2009) A structured approach to modelling the effects of binary exposure variables over the life course. International Journal of Epidemiology 38, 528537.Google Scholar
Muris, P, Meesters, C and Van Den Berg, F (2003) The Strengths and Difficulties Questionnaire (SDQ) – further evidence for its reliability and validity in a community sample of Dutch children and adolescents. European Child & Adolescent Psychiatry 12, 18.Google Scholar
Murray, J and Murray, L (2010) Parental incarceration, attachment and child psychopathology. Attachment & Human Development 12, 289309.Google Scholar
Najman, JM, Clavarino, A, Mcgee, TR, Bor, W, Williams, GM and Hayatbakhsh, MR (2010 a). Timing and chronicity of family poverty and development of unhealthy behaviors in children: a longitudinal study. Journal of Adolescent Health 46, 538544.Google Scholar
Najman, JM, Hayatbakhsh, MR, Clavarino, A, Bor, W, O'CALLAGHAN, MJ and Williams, GM (2010 b). Family poverty over the early life course and recurrent adolescent and young adult anxiety and depression: a longitudinal study. American Journal of Public Health 100, 17191723.Google Scholar
Norman, RE, Byambaa, M, De, R, Butchart, A, Scott, J and Vos, T (2012) The long-term health consequences of child physical abuse, emotional abuse, and neglect: a systematic review and meta-analysis. PLOS Medicine 9, e1001349.Google Scholar
Podsakoff, PM, Mackenzie, SB, Lee, JY and Podsakoff, NP (2003) Common method biases in behavioral research: a critical review of the literature and recommended remedies. Journal of Applied Psychology 88, 879903.Google Scholar
Raineki, C, Cortes, MR, Belnoue, L and Sullivan, RM (2012) Effects of early-life abuse differ across development: infant social behavior deficits are followed by adolescent depressive-like behaviors mediated by the amygdala. Journal of Neuroscience 32, 77587765.Google Scholar
Ringoot, AP, Tiemeier, H, Jaddoe, VW, So, P, Hofman, A, Verhulst, FC et al. (2015) Parental depression and child well-being: young children's self-reports helped addressing biases in parent reports. Journal of Clinical Epidemiology 68, 928938.Google Scholar
Rutter, M, Maughan, B, Mortimore, P and Outston, J (1979) Fifteen Thousand Hours: Secondary Schools and their Effects on Children. Cambridge, MA: Harvard University Press.Google Scholar
Sanchez, MM, Ladd, CO and Plotsky, PM (2001) Early adverse experience as a developmental risk factor for later psychopathology: evidence from rodent and primate models. Development and Psychopathology 13, 419449.Google Scholar
Shanahan, L, Copeland, WE, Costello, EJ and Angold, A (2011) Child-, adolescent- and young adult-onset depressions: differential risk factors in development? Psychological Medicine 41, 22652274.Google Scholar
Shonkoff, JP and Garner, AS (2012) The lifelong effects of early childhood adversity and toxic stress. Pediatrics 129, e232e246.Google Scholar
Slopen, N, Koenen, KC and Kubzansky, LD (2014) Cumulative adversity in childhood and emergent risk factors for long-term health. Journal of Pediatrics 164, 631638.Google Scholar
Slopen, N, Kubzansky, LD, McLaughlin, KA and Koenen, KC (2012) Childhood adversity and inflammatory processes in youth: a prospective study. Psychoneuroendocrinology 38, 188200.Google Scholar
Smith, AD, Hardy, R, Heron, J, Joinson, CJ, Lawlor, DA, Macdonald-Wallis, C et al. (2016) A structured approach to hypotheses involving continuous exposures over the life course. International Journal of Epidemiology 45, 12711279.Google Scholar
Smith, AD, Heron, J, Mishra, G, Gilthorpe, MS, Ben-Shlomo, Y and Tilling, K (2015) Model selection of the effect of binary exposures over the life course. Epidemiology 26, 719726.Google Scholar
Suren, P, Gunnes, N, Roth, C, Bresnahan, M, Hornig, M, Hirtz, D et al. (2014) Parental obesity and risk of autism spectrum disorder. Pediatrics 133, e1128e1138.Google Scholar
Thornberry, TP, Henry, KL, Ireland, TO and Smith, CA (2010) The causal impact of childhood-limited maltreatment and adolescent maltreatment on early adult adjustment. Journal of Adolescent Health 46, 359365.Google Scholar
Thornberry, TP, Ireland, TO and Smith, CA (2001) The importance of timing: the varying impact of childhood and adolescent maltreatment on multiple problem outcomes. Development and Psychopathology 13, 957979.Google Scholar
Turney, K (2014) The consequences of paternal incarceration for maternal neglect and harsh parenting. Social Forces 92, 16071636.Google Scholar
Veenema, AH (2009) Early life stress, the development of aggression and neuroendocrine and neurobiological correlates: what can we learn from animal models. Frontiers in Neuroendocrinology 30, 497518.Google Scholar
Supplementary material: File

Dunn et al. supplementary material

Dunn et al. supplementary material 1

Download Dunn et al. supplementary material(File)
File 201 KB