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Cumulative environmental risk in early life is associated with mental disorders in childhood

Published online by Cambridge University Press:  22 July 2022

Kirstie O'Hare Open the ORCID record for Kirstie O'Hare [Opens in a new window] ,
Oliver Watkeys ,
Tyson Whitten ,
Kimberlie Dean ,
Kristin R. Laurens ,
Felicity Harris ,
Vaughan J. Carr  and
Melissa J. Green Open the ORCID record for Melissa J. Green [Opens in a new window]
Kirstie O'Hare
Affiliation:
Discipline of Psychiatry and Mental Health, University of New South Wales, Sydney, Australia
Oliver Watkeys
Affiliation:
Discipline of Psychiatry and Mental Health, University of New South Wales, Sydney, Australia
Tyson Whitten
Affiliation:
Discipline of Psychiatry and Mental Health, University of New South Wales, Sydney, Australia School of Social Sciences, University of Adelaide, Adelaide, South Australia, Australia
Kimberlie Dean
Affiliation:
Discipline of Psychiatry and Mental Health, University of New South Wales, Sydney, Australia Justice Health and Forensic Mental Health Network, Sydney, New South Wales, Australia
Kristin R. Laurens
Affiliation:
Discipline of Psychiatry and Mental Health, University of New South Wales, Sydney, Australia School of Psychology and Counselling, Queensland University of Technology (QUT), Brisbane, Australia
Felicity Harris
Affiliation:
Discipline of Psychiatry and Mental Health, University of New South Wales, Sydney, Australia
Vaughan J. Carr
Affiliation:
Discipline of Psychiatry and Mental Health, University of New South Wales, Sydney, Australia Neuroscience Research Australia, Sydney, Australia Department of Psychiatry, Monash University, Melbourne, Australia
Melissa J. Green*
Affiliation:
Discipline of Psychiatry and Mental Health, University of New South Wales, Sydney, Australia Neuroscience Research Australia, Sydney, Australia
*
Author for correspondence: Melissa J. Green, E-mail: melissa.green@unsw.edu.au
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Abstract

Background

No single environmental factor is a necessary or sufficient cause of mental disorder; multifactorial and transdiagnostic approaches are needed to understand the impact of the environment on the development of mental disorders across the life course.

Method

Using linked multi-agency administrative data for 71 932 children from the New South Wales Child Developmental Study, using logistic regression, we examined associations between 16 environmental risk factors in early life (prenatal period to <6 years of age) and later diagnoses of mental disorder recorded in health service data (from age 6 to 13 years), both individually and summed as an environmental risk score (ERS).

Results

The ERS was associated with all types of mental disorder diagnoses in a dose–response fashion, such that 2.8% of children with no exposure to any of the environmental factors (ERS = 0), compared to 18.3% of children with an ERS of 8 or more indicating exposure to 8 or more environmental factors (ERS ⩾ 8), had been diagnosed with any type of mental disorder up to age 13–14 years. Thirteen of the 16 environmental factors measured (including prenatal factors, neighbourhood characteristics and more proximal experiences of trauma or neglect) were positively associated with at least one category of mental disorder.

Conclusion

Exposure to cumulative environmental risk factors in early life is associated with an increased likelihood of presenting to health services in childhood for any kind of mental disorder. In many instances, these factors are preventable or capable of mitigation by appropriate public policy settings.

Keywords

Cumulative riskearly childhoodenvironmental risk scoremental illnessrecord linkage
Type
Original Article
Information
Psychological Medicine , Volume 53 , Issue 10 , July 2023 , pp. 4762 - 4771
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Copyright
Copyright © The Author(s), 2022. Published by Cambridge University Press

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References

Appleyard, K., Egeland, B., van Dulmen, M. H. M., & Sroufe, L. A. (2005). When more is not better: The role of cumulative risk in child behavior outcomes. Journal of Child Psychology and Psychiatry, 46, 235–245. https://doi.org/10.1111/j.1469-7610.2004.00351.x.CrossRefGoogle Scholar
Australian Bureau of Statistics. (2006). Census of population and housing: Nature and content. Australia: Australian Bureau of Statistics. Retrieved from https://www.abs.gov.au/AUSSTATS/abs@.nsf/DetailsPage/2008.02006.Google Scholar
Australian Bureau of Statistics. (2018). Australian and New Zealand offence classification (ANZSOC). Canberra: Australian Bureau of Statistics: Commonwealth of Australia. Retrieved from https://www.ausstats.abs.gov.au/Ausstats/subscriber.nsf/0/181552DD634CCCCCCA2574970016EE08/$File/12340_2008%20%28second%20edition%29.pdf.Google Scholar
Bale, T. L., Baram, T. Z., Brown, A. S., Goldstein, J. M., Insel, T. R., McCarthy, M. M., … Nestler, E. J. (2010). Early life programming and neurodevelopmental disorders. Biological Psychiatry, 68, 314–319. https://doi.org/10.1016/j.biopsych.2010.05.028.CrossRefGoogle ScholarPubMed
Bunea, I. M., Szentágotai-Tătar, A., & Miu, A. C. (2017). Early-life adversity and cortisol response to social stress: A meta-analysis. Translational Psychiatry, 7, 1274. https://doi.org/10.1038/s41398-017-0032-3.CrossRefGoogle Scholar
Cannon, T. D., Yu, C., Addington, J., Bearden, C. E., Cadenhead, K. S., Cornblatt, B. A., … Kattan, M. W. (2016). An individualized risk calculator for research in prodromal psychosis. American Journal of Psychiatry, 173, 980–988. https://doi.org/10.1176/appi.ajp.2016.15070890.CrossRefGoogle ScholarPubMed
Carr, A., Duff, H., & Craddock, F. (2018). A systematic review of reviews of the outcome of noninstitutional child maltreatment. Trauma, Violence, & Abuse, 21, 828–843. https://doi.org10.1177/1524838018801334.CrossRefGoogle ScholarPubMed
Carr, V. J., Harris, F., Raudino, A., Luo, L., Kariuki, M., Liu, E., … Green, M. J. (2016). New south wales child development study (NSW-CDS): An Australian multiagency, multigenerational, longitudinal record linkage study. BMJ Open, 6, e009023. https://doi.org/10.1136/bmjopen-2015-009023.CrossRefGoogle ScholarPubMed
Carrión, R. E., Cornblatt, B. A., Burton, C. Z., Tso, I. F., Auther, A. M., Adelsheim, S., … McFarlane, W. R. (2016). Personalized prediction of psychosis: External validation of the NAPLS-2 psychosis risk calculator with the EDIPPP project. American Journal of Psychiatry, 173, 989–996. https://doi.org/10.1176/appi.ajp.2016.15121565.CrossRefGoogle Scholar
Chittleborough, C. R., Searle, A. K., Smithers, L. G., Brinkman, S., & Lynch, J. W. (2016). How well can poor child development be predicted from early life characteristics?: A whole-of-population data linkage study. Early Childhood Research Quarterly, 35, 19–30. https://doi.org/10.1016/j.ecresq.2015.10.006.CrossRefGoogle Scholar
Cicchetti, D. (2010). Resilience under conditions of extreme stress: A multilevel perspective. World Psychiatry, 9, 145–154. https://doi.org/10.1002/j.2051-5545.2010.tb00297.x.CrossRefGoogle Scholar
Curtis, S., Pain, R., Fuller, S., Khatib, Y., Rothon, C., Stansfeld, S. A., & Daya, S. (2013). Neighbourhood risk factors for Common Mental Disorders among young people aged 10–20 years: A structured review of quantitative research. Health & Place, 20, 81–90. https://doi.org/10.1016/j.healthplace.2012.10.010.CrossRefGoogle Scholar
de Kluiver, H., Buizer-Voskamp, J. E., Dolan, C. V., & Boomsma, D. I. (2017). Paternal age and psychiatric disorders: A review. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics, 174, 202–213. https://doi.org/10.1002/ajmg.b.32508.CrossRefGoogle ScholarPubMed
Department of Health and Aged Care [Australian Government]. (2001). Measuring remoteness: Accessibility/remoteness index of Australia (ARIA). Canberra, Australia: Department of Health.Google Scholar
Dobbins, T. A., Sullivan, E. A., Roberts, C. L., & Simpson, J. M. (2012). Australian national birthweight percentiles by sex and gestational age, 1998–2007. Medical Journal of Australia, 197, 291–294. https://doi.org/10.5694/mja11.11331.CrossRefGoogle ScholarPubMed
Evans, G. W., Li, D., & Whipple, S. S. (2013). Cumulative risk and child development. Psychological Bulletin, 139, 1342. https://doi.org/10.1037/a0031808.CrossRefGoogle ScholarPubMed
Fisher, H. L., Caspi, A., Moffitt, T. E., Wertz, J., Gray, R., Newbury, J., … Arseneault, L. (2015). Measuring adolescents’ exposure to victimization: The Environmental Risk (E-Risk) Longitudinal Twin Study. Development and Psychopathology, 27, 1399–1416. https://doi.org/10.1017/S0954579415000838.CrossRefGoogle ScholarPubMed
Green, M. J., Harris, F., Laurens, K. R., Kariuki, M., Tzoumakis, S., Dean, K., … Carr, V. J. (2018). Cohort profile: The New South Wales child development study (NSW-CDS) – Wave 2 (child age 13 years). International Journal of Epidemiology, 47, 1396–1397k. https://doi.org/10.1093/ije/dyy115.CrossRefGoogle Scholar
Green, M. J., Hindmarsh, G., Kariuki, M., Laurens, K. R., Neil, A. L., Katz, I., … Carr, V. J. (2020). Mental disorders in children known to child protection services during early childhood. Medical Journal of Australia, 212, 22–28. https://doi.org/10.5694/mja2.50392.CrossRefGoogle ScholarPubMed
Guloksuz, S., Pries, L.-K., Delespaul, P., Kenis, G., Luykx, J. J., Lin, B. D., … van Os, J. (2019). Examining the independent and joint effects of molecular genetic liability and environmental exposures in schizophrenia: Results from the EUGEI study. World Psychiatry, 18, 173–182. https://doi.org/10.1002/wps.20629.CrossRefGoogle ScholarPubMed
Guloksuz, S., van Os, J., & Rutten, B. P. F. (2018). The exposome paradigm and the complexities of environmental research in psychiatry. JAMA Psychiatry, 75, 985–986. https://doi.org/10.1001/jamapsychiatry.2018.1211.CrossRefGoogle ScholarPubMed
Hughes, K., Bellis, M. A., Hardcastle, K. A., Sethi, D., Butchart, A., Mikton, C., … Dunne, M. P. (2017). The effect of multiple adverse childhood experiences on health: A systematic review and meta-analysis. The Lancet Public Health, 2, e356–e366. https://doi.org/10.1016/S2468-2667(17)30118-4.CrossRefGoogle Scholar
Kim, M. K., Lee, S. M., Bae, S.-H., Kim, H. J., Lim, N. G., Yoon, S.-J., … Jo, M.-W. (2018). Socioeconomic status can affect pregnancy outcomes and complications, even with a universal healthcare system. International Journal for Equity in Health, 17, 2. https://doi.org/10.1186/s12939-017-0715-7.CrossRefGoogle ScholarPubMed
Kim-Cohen, J., Caspi, A., Moffitt, T. E., Harrington, H., Milne, B. J., & Poulton, R. (2003). Prior juvenile diagnoses in adults with mental disorder: Developmental follow-back of a prospective-longitudinal cohort. Archives of General Psychiatry, 60, 709–717. https://doi.org/10.1001/archpsyc.60.7.709.CrossRefGoogle ScholarPubMed
Lee, R. D., Fang, X., & Luo, F. (2013). The impact of parental incarceration on the physical and mental health of young adults. Pediatrics, 131, e1188–e1195. https://doi.org/10.1542/peds.2012-0627.CrossRefGoogle ScholarPubMed
Madsen, K. B., Ersbøll, A. K., Olsen, J., Parner, E., & Obel, C. (2015). Geographic analysis of the variation in the incidence of ADHD in a country with free access to healthcare: A Danish cohort study. International Journal of Health Geographics, 14, 24. https://doi.org/10.1186/s12942-015-0018-4.CrossRefGoogle Scholar
Mas, S., Boloc, D., Rodríguez, N., Mezquida, G., Amoretti, S., Cuesta, M. J., … PEPs Group. (2020). Examining gene–environment interactions using aggregate scores in a first-episode psychosis cohort. Schizophrenia Bulletin, 46, 1019–1025. https://doi.org/10.1093/schbul/sbaa012.CrossRefGoogle Scholar
McGrath, J. J., & Welham, J. L. (1999). Season of birth and schizophrenia: A systematic review and meta-analysis of data from the Southern Hemisphere (Details of this paper were presented at the Winter Workshop on Schizophrenia Research, Davos, Switzerland, February 1998.). Schizophrenia Research, 35, 237–242. https://doi.org/10.1016/S0920-9964(98)00139-X.CrossRefGoogle Scholar
McLaughlin, K. A., Conron, K. J., Koenen, K. C., & Gilman, S. E. (2010). Childhood adversity, adult stressful life events, and risk of past-year psychiatric disorder: A test of the stress sensitization hypothesis in a population-based sample of adults. Psychological Medicine, 40, 1647–1658. https://doi.org/10.1017/S0033291709992121.CrossRefGoogle Scholar
Mendoza Diaz, A., Burman, C., Finlay Jones, A., Short, K., Woolfenden, S., Downs, J., & Eapen, V. (2020). First 2000 days overview. Australia: NSW Health. Retrieved from https://www.health.nsw.gov.au/kidsfamilies/programs/Factsheets/brighter-beginnings.pdf.Google Scholar
Moore, T. M., Calkins, M. E., Rosen, A. F. G., Butler, E. R., Ruparel, K., Fusar-Poli, P., … Gur, R. E. (2021). Development of a probability calculator for psychosis risk in children, adolescents, and young adults. Psychological Medicine, 1–9. https://doi.org/10.1017/S0033291720005231.Google ScholarPubMed
Nolen-Hoeksema, S., & Watkins, E. R. (2011). A heuristic for developing transdiagnostic models of psychopathology: Explaining multifinality and divergent trajectories. Perspectives on Psychological Science, 6, 589–609. https://doi.org/10.1177/1745691611419672.CrossRefGoogle ScholarPubMed
NSW Bureau of Crime Statistics and Research. (2020). Offence open data: Recorded criminal incident by month – by postcode. NSW Bureau of Crime Statistics and Research. Retrieved from https://www.bocsar.nsw.gov.au/Pages/bocsar_datasets/Offence.aspx.Google Scholar
Padmanabhan, J. L., Shah, J. L., Tandon, N., & Keshavan, M. S. (2017). The ‘polyenviromic risk score’: Aggregating environmental risk factors predicts conversion to psychosis in familial high-risk subjects. Schizophrenia Research, 181, 17–22. https://doi.org/10.1016/j.schres.2016.10.014.CrossRefGoogle ScholarPubMed
Paradies, Y. (2018). Racism and indigenous health. In Oxford research encyclopedia of global public health. Retrieved from https://doi.org/10.1093/acrefore/9780190632366.013.86.Google Scholar
Pink, B. (2013). Socio-economic indexes for areas (SEIFA) 2011. Canberra: Australian Bureau of Statistics.Google Scholar
Pries, L.-K., Guloksuz, S., ten Have, M., de Graaf, R., van Dorsselaer, S., Gunther, N., … van Os, J. (2018). Evidence that environmental and familial risks for psychosis additively impact a multidimensional subthreshold psychosis syndrome. Schizophrenia Bulletin, 44, 710–719. https://doi.org/10.1093/schbul/sby051.CrossRefGoogle ScholarPubMed
Pries, L.-K., Lage-Castellanos, A., Delespaul, P., Kenis, G., Luykx, J. J., Lin, B. D., … Guloksuz, S. (2019). Estimating exposome score for schizophrenia using predictive modeling approach in two independent samples: The results from the EUGEI study. Schizophrenia Bulletin, 45, 960–965. https://doi.org/10.1093/schbul/sbz054.CrossRefGoogle Scholar
Roffman, J. L., Sipahi, E. D., Dowling, K. F., Hughes, D. E., Hopkinson, C. E., Lee, H., … Dunn, E. C. (2021). Association of adverse prenatal exposure burden with child psychopathology in the adolescent brain cognitive development (ABCD) study. PLoS One, 16, e0250235. https://doi.org/10.1371/journal.pone.0250235.CrossRefGoogle ScholarPubMed
Rutten, B. P. F., Hammels, C., Geschwind, N., Menne-Lothmann, C., Pishva, E., Schruers, K., … Wichers, M. (2013). Resilience in mental health: Linking psychological and neurobiological perspectives. Acta Psychiatrica Scandinavica, 128, 3–20. https://doi.org/10.1111/acps.12095.CrossRefGoogle ScholarPubMed
Sameroff, A. (2006). Identifying risk and protective factors for healthy child development. In Clarke-Stewart, A. & Dunn, J. (Eds.), Families count: Effects on child and adolescent development (pp. 53–76). Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Saunders, N. R., Janus, M., Porter, J., Lu, H., Gaskin, A., Kalappa, G., & Guttmann, A. (2021). Use of administrative record linkage to measure medical and social risk factors for early developmental vulnerability in Ontario, Canada. International Journal of Population Data Science, 6, 1407–1407. https://doi.org/10.23889/ijpds.v6i1.1407.CrossRefGoogle ScholarPubMed
Starr, L. R., Hammen, C., Conway, C. C., Raposa, E., & Brennan, P. A. (2014). Sensitizing effect of early adversity on depressive reactions to later proximal stress: Moderation by polymorphisms in serotonin transporter and corticotropin-releasing hormone receptor genes in a 20-year longitudinal study. Developmental Psychopathology, 26, 1241–1254. https://doi.org/10.1017/s0954579414000996.CrossRefGoogle Scholar
Stepniak, B., Papiol, S., Hammer, C., Ramin, A., Everts, S., Hennig, L., … Ehrenreich, H. (2014). Accumulated environmental risk determining age at schizophrenia onset: A deep phenotyping-based study. The Lancet Psychiatry, 1, 444–453. https://doi.org/10.1016/S2215-0366(14)70379-7.CrossRefGoogle ScholarPubMed
Stilo, S. A., Gayer-Anderson, C., Beards, S., Hubbard, K., Onyejiaka, A., Keraite, A., … Morgan, C. (2017). Further evidence of a cumulative effect of social disadvantage on risk of psychosis. Psychological Medicine, 47, 913–924. https://doi.org/10.1017/S0033291716002993.CrossRefGoogle ScholarPubMed
Theall, K. P., Drury, S. S., & Shirtcliff, E. A. (2012). Cumulative neighborhood risk of psychosocial stress and allostatic load in adolescents. American Journal of Epidemiology, 176, S164–S174. https://doi.org/10.1093/aje/kws185.CrossRefGoogle ScholarPubMed
Uher, R., & Zwicker, A. (2017). Etiology in psychiatry: Embracing the reality of poly-gene-environmental causation of mental illness. World Psychiatry, 16, 121–129. https://doi.org/10.1002/wps.20436.CrossRefGoogle ScholarPubMed
Vassos, E., Sham, P., Kempton, M., Trotta, A., Stilo, S. A., Gayer-Anderson, C., … Morgan, C. (2020). The Maudsley environmental risk score for psychosis. Psychological Medicine, 50, 2213–2220. https://doi.org/10.1017/S0033291719002319.CrossRefGoogle ScholarPubMed
Wickham, H. (2016). Ggplot2: Elegant graphics for data analysis. Springer International Publishing.CrossRefGoogle Scholar
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