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

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 theo...

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Vydáno v:	Psychological medicine Ročník 48; číslo 15; s. 2562 - 2572
Hlavní autoři:	Dunn, Erin C., Soare, Thomas W., Raffeld, Miriam R., Busso, Daniel S., Crawford, Katherine M., Davis, Kathryn A., Fisher, Virginia A., Slopen, Natalie, Smith, Andrew D.A.C., Tiemeier, Henning, Susser, Ezra S.
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Cambridge, UK Cambridge University Press 01.11.2018
Témata:	Abuse Accumulation Adverse childhood experiences Adverse Childhood Experiences - statistics & numerical data Adversity Age Boys Caregiver burden Caregivers Child Child Abuse - statistics & numerical data Child, Preschool Childbirth & labor Childhood Children Children & youth Critical period Data dictionaries Economic stress Emotional abuse Emotions Ethics Female Girls Health status Humans Infant Life course Longitudinal Studies Male Mathematical models Mental disorders Mental Disorders - epidemiology Mental Disorders - etiology Mental health Models, Statistical Original Articles Parent-child relations Parents & parenting Psychopathology Questionnaires Recency Sexual abuse Stress Symptoms United Kingdom - epidemiology Variability United Kingdom Childhood adversity sensitive period accumulation psychopathology recency life course
ISSN:	0033-2917, 1469-8978, 1469-8978
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Abstract	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. 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. 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). 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.
AbstractList	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. 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. 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). 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. 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.BACKGROUNDAlthough 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.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.METHODSProspective 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.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).RESULTSRecency 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).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.CONCLUSIONSChild 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. BackgroundAlthough 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.MethodsProspective 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.ResultsRecency 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).ConclusionsChild 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.
Author	Tiemeier, Henning Busso, Daniel S. Raffeld, Miriam R. Smith, Andrew D.A.C. Susser, Ezra S. Soare, Thomas W. Fisher, Virginia A. Davis, Kathryn A. Slopen, Natalie Crawford, Katherine M. Dunn, Erin C.
AuthorAffiliation	4 Harvard Graduate School of Education, Cambridge, MA 2 Department of Psychiatry, Harvard Medical School, Boston, MA 8 Applied Statistics Group, University of the West of England, Bristol, UK 10 New York State Psychiatric Institute, New York, NY 3 Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 5 Department of Biostatistics, Boston University School of Public Health, Boston, MA 6 Department of Epidemiology and Biostatistics, School of Public Health, University of Maryland, College Park, MD 7 Erasmus Medical Center, Rotterdam, The Netherlands 1 Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 9 Department of Epidemiology, Mailman School of Public Health, Columbia University
AuthorAffiliation_xml	– name: 6 Department of Epidemiology and Biostatistics, School of Public Health, University of Maryland, College Park, MD – name: 4 Harvard Graduate School of Education, Cambridge, MA – name: 5 Department of Biostatistics, Boston University School of Public Health, Boston, MA – name: 8 Applied Statistics Group, University of the West of England, Bristol, UK – name: 10 New York State Psychiatric Institute, New York, NY – name: 9 Department of Epidemiology, Mailman School of Public Health, Columbia University – name: 1 Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA – name: 3 Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA – name: 7 Erasmus Medical Center, Rotterdam, The Netherlands – name: 2 Department of Psychiatry, Harvard Medical School, Boston, MA
Author_xml	– sequence: 1 givenname: Erin C. surname: Dunn fullname: Dunn, Erin C. email: edunn2@mgh.Harvard.edu organization: 1Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA – sequence: 2 givenname: Thomas W. surname: Soare fullname: Soare, Thomas W. organization: 1Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA – sequence: 3 givenname: Miriam R. surname: Raffeld fullname: Raffeld, Miriam R. organization: 1Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA – sequence: 4 givenname: Daniel S. surname: Busso fullname: Busso, Daniel S. organization: 1Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA – sequence: 5 givenname: Katherine M. surname: Crawford fullname: Crawford, Katherine M. organization: 1Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA – sequence: 6 givenname: Kathryn A. surname: Davis fullname: Davis, Kathryn A. organization: 1Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA – sequence: 7 givenname: Virginia A. surname: Fisher fullname: Fisher, Virginia A. organization: 1Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA – sequence: 8 givenname: Natalie surname: Slopen fullname: Slopen, Natalie organization: 6Department of Epidemiology and Biostatistics, School of Public Health, University of Maryland, College Park, MD, USA – sequence: 9 givenname: Andrew D.A.C. surname: Smith fullname: Smith, Andrew D.A.C. organization: 7Applied Statistics Group, University of the West of England, Bristol, UK – sequence: 10 givenname: Henning surname: Tiemeier fullname: Tiemeier, Henning organization: 8Erasmus Medical Center, Rotterdam, The Netherlands – sequence: 11 givenname: Ezra S. surname: Susser fullname: Susser, Ezra S. organization: 9Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, USA
BackLink	https://www.ncbi.nlm.nih.gov/pubmed/29478418$$D View this record in MEDLINE/PubMed
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Snippet	Although childhood adversity is a potent determinant of psychopathology, relatively little is known about how the characteristics of adversity exposure,... BackgroundAlthough childhood adversity is a potent determinant of psychopathology, relatively little is known about how the characteristics of adversity...
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SubjectTerms	Abuse Accumulation Adverse childhood experiences Adverse Childhood Experiences - statistics & numerical data Adversity Age Boys Caregiver burden Caregivers Child Child Abuse - statistics & numerical data Child, Preschool Childbirth & labor Childhood Children Children & youth Critical period Data dictionaries Economic stress Emotional abuse Emotions Ethics Female Girls Health status Humans Infant Life course Longitudinal Studies Male Mathematical models Mental disorders Mental Disorders - epidemiology Mental Disorders - etiology Mental health Models, Statistical Original Articles Parent-child relations Parents & parenting Psychopathology Questionnaires Recency Sexual abuse Stress Symptoms United Kingdom - epidemiology Variability
Title	What life course theoretical models best explain the relationship between exposure to childhood adversity and psychopathology symptoms: recency, accumulation, or sensitive periods?
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