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Parent-child nativity, race, ethnicity, and mental health conditions among U.S. children
- K. Zarei, L. Kahle, D. Buckman, K. Choi, F. Williams
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- Journal:
- European Psychiatry / Volume 66 / Issue S1 / March 2023
- Published online by Cambridge University Press:
- 19 July 2023, p. S65
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Introduction
Over a quarter of U.S. children have at least one immigrant parent. Mental health disparities in children need to be assessed to better identify disproportionate burdens and promote health equity.
ObjectivesTo assess the associations between race, ethnicity, and parent-child nativity, and mental health conditions in the U.S.
MethodsData were from the 2016-2019 National Survey of Children’s Health (n=114,476 children aged 3-17 years), a nationwide, cross-sectional survey. Outcome variables included three mental health conditions (depression, anxiety, and behavior or conduct problems) reported by the parent/guardian. Additional measures included questions about healthcare access and use, demographics, and nine household challenge adverse childhood experiences (ACEs) used to quantify a total ACE score (0-9). Information on nativity was used to define immigrant generation (1st, 2nd, and 3rd+). Weighted logistic regression was used to assess the associations between race/ethnicity (Asian, Black, Hispanic, White, and Other), household generation, and outcome variables, among children who reported access to or utilized health services, adjusting for demographics. Multiple imputation was used to handle missing data.
ResultsAsian, Black, Hispanic, and White 3rd+ generation children had increased odds of depression compared to their 1st generation counterparts, same as among White, 2nd generation children. Race/ethnicity was not associated with depression among 1st and 3rd+ generation children, but Asian, Black, and Hispanic children had lower odds of depression compared to White children among 2nd generation children. Asian, Black, Hispanic, and Other-race 3rd+ generation children had increased odds of anxiety compared to their 1st generation counterparts, with similar findings also observed for Black and Other-race 2nd generation children. Being racial/ethnic minorities was generally associated with decreased odds of anxiety among 1st and 2nd generation children compared to White children from the respective generations. Asian, Black, Hispanic, and Other-race 3rd+ generation children had increased odds of behavior/conduct problems compared to their 1st generation counterparts. The observed associations remained significant after adjusting for the modified ACE score.
ConclusionsWe found significant differences in several mental health conditions in children by parent-child nativity, race, and ethnicity that could not be explained by demographics, childhood adversity, and healthcare access and use. Lower odds of mental health conditions among minority children could represent differences due to factors such as differential reporting, and higher odds of mental health conditions, including in third- and higher generation children, need further investigation to develop approaches to promote mental health equity.
Disclosure of InterestNone Declared
Role of age, gender and marital status in prognosis for adults with depression: An individual patient data meta-analysis
- J. E. J. Buckman, R. Saunders, J. Stott, L.-L. Arundell, C. O'Driscoll, M. R. Davies, T. C. Eley, S. D. Hollon, T. Kendrick, G. Ambler, Z. D. Cohen, E. Watkins, S. Gilbody, N. Wiles, D. Kessler, D. Richards, S. Brabyn, E. Littlewood, R. J. DeRubeis, G. Lewis, S. Pilling
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- Journal:
- Epidemiology and Psychiatric Sciences / Volume 30 / 2021
- Published online by Cambridge University Press:
- 04 June 2021, e42
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Aims
To determine whether age, gender and marital status are associated with prognosis for adults with depression who sought treatment in primary care.
MethodsMedline, Embase, PsycINFO and Cochrane Central were searched from inception to 1st December 2020 for randomised controlled trials (RCTs) of adults seeking treatment for depression from their general practitioners, that used the Revised Clinical Interview Schedule so that there was uniformity in the measurement of clinical prognostic factors, and that reported on age, gender and marital status. Individual participant data were gathered from all nine eligible RCTs (N = 4864). Two-stage random-effects meta-analyses were conducted to ascertain the independent association between: (i) age, (ii) gender and (iii) marital status, and depressive symptoms at 3–4, 6–8,<Vinod: Please carry out the deletion of serial commas throughout the article> and 9–12 months post-baseline and remission at 3–4 months. Risk of bias was evaluated using QUIPS and quality was assessed using GRADE. PROSPERO registration: CRD42019129512. Pre-registered protocol https://osf.io/e5zup/.
ResultsThere was no evidence of an association between age and prognosis before or after adjusting for depressive ‘disorder characteristics’ that are associated with prognosis (symptom severity, durations of depression and anxiety, comorbid panic disorderand a history of antidepressant treatment). Difference in mean depressive symptom score at 3–4 months post-baseline per-5-year increase in age = 0(95% CI: −0.02 to 0.02). There was no evidence for a difference in prognoses for men and women at 3–4 months or 9–12 months post-baseline, but men had worse prognoses at 6–8 months (percentage difference in depressive symptoms for men compared to women: 15.08% (95% CI: 4.82 to 26.35)). However, this was largely driven by a single study that contributed data at 6–8 months and not the other time points. Further, there was little evidence for an association after adjusting for depressive ‘disorder characteristics’ and employment status (12.23% (−1.69 to 28.12)). Participants that were either single (percentage difference in depressive symptoms for single participants: 9.25% (95% CI: 2.78 to 16.13) or no longer married (8.02% (95% CI: 1.31 to 15.18)) had worse prognoses than those that were married, even after adjusting for depressive ‘disorder characteristics’ and all available confounders.
ConclusionClinicians and researchers will continue to routinely record age and gender, but despite their importance for incidence and prevalence of depression, they appear to offer little information regarding prognosis. Patients that are single or no longer married may be expected to have slightly worse prognoses than those that are married. Ensuring this is recorded routinely alongside depressive ‘disorder characteristics’ in clinic may be important.
Predicting prognosis for adults with depression using individual symptom data: a comparison of modelling approaches
- J. E. J. Buckman, Z. D. Cohen, C. O'Driscoll, E. I. Fried, R. Saunders, G. Ambler, R. J. DeRubeis, S. Gilbody, S. D. Hollon, T. Kendrick, E. Watkins, T.C. Eley, A. J. Peel, C. Rayner, D. Kessler, N. Wiles, G. Lewis, S. Pilling
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- Journal:
- Psychological Medicine / Volume 53 / Issue 2 / January 2023
- Published online by Cambridge University Press:
- 06 May 2021, pp. 408-418
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Background
This study aimed to develop, validate and compare the performance of models predicting post-treatment outcomes for depressed adults based on pre-treatment data.
MethodsIndividual patient data from all six eligible randomised controlled trials were used to develop (k = 3, n = 1722) and test (k = 3, n = 918) nine models. Predictors included depressive and anxiety symptoms, social support, life events and alcohol use. Weighted sum scores were developed using coefficient weights derived from network centrality statistics (models 1–3) and factor loadings from a confirmatory factor analysis (model 4). Unweighted sum score models were tested using elastic net regularised (ENR) and ordinary least squares (OLS) regression (models 5 and 6). Individual items were then included in ENR and OLS (models 7 and 8). All models were compared to one another and to a null model (mean post-baseline Beck Depression Inventory Second Edition (BDI-II) score in the training data: model 9). Primary outcome: BDI-II scores at 3–4 months.
ResultsModels 1–7 all outperformed the null model and model 8. Model performance was very similar across models 1–6, meaning that differential weights applied to the baseline sum scores had little impact.
ConclusionsAny of the modelling techniques (models 1–7) could be used to inform prognostic predictions for depressed adults with differences in the proportions of patients reaching remission based on the predicted severity of depressive symptoms post-treatment. However, the majority of variance in prognosis remained unexplained. It may be necessary to include a broader range of biopsychosocial variables to better adjudicate between competing models, and to derive models with greater clinical utility for treatment-seeking adults with depression.
The contribution of depressive ‘disorder characteristics’ to determinations of prognosis for adults with depression: an individual patient data meta-analysis
- Joshua E. J. Buckman, Rob Saunders, Zachary D. Cohen, Phoebe Barnett, Katherine Clarke, Gareth Ambler, Robert J. DeRubeis, Simon Gilbody, Steven D. Hollon, Tony Kendrick, Edward Watkins, Nicola Wiles, David Kessler, David Richards, Deborah Sharp, Sally Brabyn, Elizabeth Littlewood, Chris Salisbury, Ian R. White, Glyn Lewis, Stephen Pilling
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- Journal:
- Psychological Medicine / Volume 51 / Issue 7 / May 2021
- Published online by Cambridge University Press:
- 14 April 2021, pp. 1068-1081
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Background
This study aimed to investigate general factors associated with prognosis regardless of the type of treatment received, for adults with depression in primary care.
MethodsWe searched Medline, Embase, PsycINFO and Cochrane Central (inception to 12/01/2020) for RCTs that included the most commonly used comprehensive measure of depressive and anxiety disorder symptoms and diagnoses, in primary care depression RCTs (the Revised Clinical Interview Schedule: CIS-R). Two-stage random-effects meta-analyses were conducted.
ResultsTwelve (n = 6024) of thirteen eligible studies (n = 6175) provided individual patient data. There was a 31% (95%CI: 25 to 37) difference in depressive symptoms at 3–4 months per standard deviation increase in baseline depressive symptoms. Four additional factors: the duration of anxiety; duration of depression; comorbid panic disorder; and a history of antidepressant treatment were also independently associated with poorer prognosis. There was evidence that the difference in prognosis when these factors were combined could be of clinical importance. Adding these variables improved the amount of variance explained in 3–4 month depressive symptoms from 16% using depressive symptom severity alone to 27%. Risk of bias (assessed with QUIPS) was low in all studies and quality (assessed with GRADE) was high. Sensitivity analyses did not alter our conclusions.
ConclusionsWhen adults seek treatment for depression clinicians should routinely assess for the duration of anxiety, duration of depression, comorbid panic disorder, and a history of antidepressant treatment alongside depressive symptom severity. This could provide clinicians and patients with useful and desired information to elucidate prognosis and aid the clinical management of depression.
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