Association of Multigenerational Family History of Depression With Lifetime Depressive and Other Psychiatric Disorders in Children: Results from the Adolescent Brain Cognitive Development (ABCD) Study

Milenna T van Dijk; Eleanor Murphy; Jonathan E Posner; Ardesheer Talati; Myrna M Weissman

doi:10.1001/jamapsychiatry.2021.0350

. 2021 Apr 21;78(7):1–11. doi: 10.1001/jamapsychiatry.2021.0350

Association of Multigenerational Family History of Depression With Lifetime Depressive and Other Psychiatric Disorders in Children

Results from the Adolescent Brain Cognitive Development (ABCD) Study

Milenna T van Dijk ^1,², Eleanor Murphy ^1,², Jonathan E Posner ^1,³, Ardesheer Talati ^1,², Myrna M Weissman ^1,^2,^4,^✉

¹Department of Psychiatry, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, New York

²Division of Translational Epidemiology, New York State Psychiatric Institute, New York

³Division of Child and Adolescent Psychiatry, New York State Psychiatric Institute, New York

⁴Mailman School of Public Health, Columbia University, New York, New York

Accepted for Publication: February 12, 2021.

Published Online: April 21, 2021. doi:10.1001/jamapsychiatry.2021.0350

^✉

Corresponding Author: Myrna M. Weissman, PhD, Division of Translational Epidemiology, New York State Psychiatric Institute, 1051 Riverside Dr, Unit 24, New York, NY 10032 (myrna.weissman@nyspi.columbia.edu).

Author Contributions: Drs van Dijk and Murphy had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Drs van Dijk and Murphy are co–first authors and contributed equally to this work.

Study concept and design: van Dijk, Posner, Talati, Weissman.

Acquisition, analysis, or interpretation of data: van Dijk, Murphy, Talati, Weissman.

Drafting of the manuscript: van Dijk, Murphy, Posner, Talati.

Critical revision of the manuscript for important intellectual content: van Dijk, Murphy, Talati, Weissman.

Statistical analysis: van Dijk, Murphy.

Obtained funding: Posner, Weissman.

Administrative, technical, or material support: Murphy.

Study supervision: Posner, Talati, Weissman.

Conflict of Interest Disclosures: Dr Posner has received research support from Shire Pharmaceuticals and Aevi Genomics. Dr Weissman has received research funding from the National Institute of Mental Health, Brain and Behavior Foundation, Templeton Foundation, and the Sackler Foundation; book royalties from Perseus Press, Oxford Press, and APA Publishing; and royalties on the social adjustment scale from Multihealth Systems. No other disclosures were reported.

Funding/Support: This work is supported by grant R01 MH-036197 from the National Institute of Mental Health (principal investigators: Drs Posner and Weissman).

Role of the Funder/Sponsor: The funder had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Disclaimer: ABCD Consortium Investigators designed and implemented the study and/or provided data but did not necessarily participate in analysis or writing of this report. This manuscript reflects the views of the authors and may not reflect the opinions or views of the National Institutes of Health or ABCD Consortium Investigators.

Additional Information: Data used in the preparation of this article were obtained from the Adolescent Brain Cognitive Development (ABCD) study held in the National Institute of Mental Health Data Archive. This is a multisite, longitudinal study designed to recruit more than 10 000 children aged 9 to 10 years and observe them for 10 years into early adulthood. The ABCD study is supported by the National Institutes of Health and additional federal partners under award numbers U01DA041048, U01DA050989, U01DA051016, U01DA041022, U01DA051018, U01DA051037, U01DA050987, U01DA041174, U01DA041106, U01DA041117, U01DA041028, U01DA041134, U01DA050988, U01DA051039, U01DA041156, U01DA041025, U01DA041120, U01DA051038, U01DA041148, U01DA041093, U01DA041089, U24DA041123, and U24DA041147. A full list of supporters is available at https://abcdstudy.org/federal-partners/. A listing of participating sites and a complete listing of the study investigators can be found at https://abcdstudy.org/consortium_members/. The ABCD data repository grows and changes over time. The ABCD data used in this report came from version 2.01.

^✉

Corresponding author.

PMCID: PMC8060885 PMID: 33881474

Key Points

Question

Does having multiple prior generations affected by depression increase risk of psychopathology in children, and can it be reliably measured in large, diverse samples using informant-reported family history?

Findings

In this secondary analysis of the Adolescent Brain Cognitive Development study including 11 200 children from 9462 families, the highest risks of depressive and other psychiatric disorders were found in children with 2 depression-affected generations compared with those with 1 or no affected generations. This pattern held across sex, socioeconomic status, and race/ethnicity.

Meaning

In this study, family history methods across 3 generations were associated with increased psychiatric risk in offspring and may enable selection of homogenous samples for genetic and biological studies as well as development of screening tools in applied mental health settings.

This secondary analysis of the Adolescent Brain Cognitive Development study examines the association of multigenerational family history of depression with lifetime depressive disorders and other psychopathology in children.

Abstract

Importance

Three-generation family studies of depression have established added risk of psychopathology for offspring with 2 previous generations affected with depression compared with 1 or none. Because of their rigorous methodology, there are few of these studies, and existing studies are limited by sample sizes. Consequently, the 3-generation family risk paradigm established in family studies can be a critical neuropsychiatric tool if similar transmission patterns are reliably demonstrated with the family history method.

Objective

To examine the association of multigenerational family history of depression with lifetime depressive disorders and other psychopathology in children.

Design, Setting, and Participants

In this analysis of the Adolescent Brain Cognitive Development (ABCD) study data, retrospective, cross-sectional reports on psychiatric functioning among 11 200 children (generation 3 [G3]) and parent reports on parents’ (G2) and grandparents’ (G1) depression histories were analyzed. The ABCD study sampling weights were used for generalized estimating equation models and descriptive analyses. Data were collected from September 2016 to November 2018, and data were analyzed from July to November 2020.

Main Outcomes and Measures

Four risk categories were created, reflecting how many prior generations had history of depression: (1) neither G1 nor G2 (G1−/G2−), (2) only G1 (G1+/G2−), (3) only G2 (G1−/G2+), and (4) both G1 and G2 (G1+/G2+). Child lifetime prevalence and relative risks of psychiatric disorders were based on child and caregiver reports and grouped according to familial risk category derived from G1 and G2 depression history.

Results

Among 11 200 included children, 5355 (47.8%) were female, and the mean (SD) age was 9.9 (0.6) years. By parent reports, the weighted prevalence of depressive disorder among children was 3.8% (95% CI, 3.2-4.3) for G1−/G2− children, 5.5% (95% CI, 4.3-7.1) for G1+/G2− children, 10.4% (95% CI, 8.6-12.6) for G1−/G2+ children, and 13.3% (95% CI, 11.6-15.2) for G1+/G2+ children (Cochran-Armitage trend = 243.77; P < .001). The weighted suicidal behavior prevalence among children was 5.0% (95% CI, 4.5-5.6) for G1−/G2− children, 7.2% (95% CI, 5.8-8.9) for G1+/G2− children, 12.1% (95% CI, 10.1-14.4) for G1−/G2+ children, and 15.0% (95% CI, 13.2-17.0) for G1+/G2+ children (Cochran-Armitage trend = 188.66; P < .001). By child reports, the weighted prevalence of depressive disorder was 4.8% (95% CI, 4.3-5.5) for G1−/G2− children, 4.3% (95% CI, 3.2-5.7) for G1+/G2− children, 6.3% (95% CI, 4.9-8.1) for G1−/G2+ children, and 7.0% (95% CI, 5.8-8.5) for G1+/G2+ children (Cochran-Armitage trend = 9.01; P = .002), and the weighted prevalence of suicidal behaviors was 7.4% (95% CI, 6.7-8.2) for G1−/G2− children, 7.0% (95% CI, 5.6-8.6) for G1+/G2− children, 9.8% (95% CI, 8.1-12.0) for G1−/G2+ children, and 13.8% (95% CI, 12.1-15.8) for G1+/G2+ children (Cochran-Armitage trend = 46.69; P < .001). Similar patterns were observed for other disorders for both parent and child reports and across sex, socioeconomic status, and race/ethnicity.

Conclusions and Relevance

In this study, having multiple prior affected generations was associated with increased risk of childhood psychopathology. Furthermore, these findings were detectable even at prepubertal ages and existed in diverse racial/ethnic and socioeconomic groups. Clinically, they underscore the need for screening for family history in pediatric settings and highlight implications for biological research with homogenous subgroups using magnetic resonance imaging or genetic analyses.

Introduction

Family history is among the most reliable risk markers for future mental illness.^1,2 The biological offspring of parents with depression have a 2-fold to 5-fold increased risk of major depressive disorder (MDD), other nonpsychotic disorders, and unnatural deaths.^3,4,5,6,7,8 These disorders often begin in childhood or adolescence and are sustained over a life course with recurrences and remission as well as impaired social functioning.^3,9 Family history also predicts stable brain-based differences, such as cortical thinning,^10,11,12,13 smaller subcortical volumes,^14,15,16 and altered resting-state functional connectivity,^17,18 even in high-risk offspring who never develop psychopathology.

We are aware of just 2 studies^19,20 that assessed the association of 2 prior generations of depression in the family with the prevalence of grandchild psychiatric diagnoses. The first is a 3-generation study observing family members for up to 38 years conducted by Weissman and colleagues¹⁹ (high-risk study). Grandchildren with 2 previous generations affected by MDD were at highest risk, with 3-fold risk of developing MDD, 2-fold risk of having suicidal thoughts and behaviors, and increased other psychopathology. Furthermore, high-risk offspring had altered hippocampal microstructure, which predicted follow-up depressive symptoms, and individuals with 2 previous generations of depression had the most pronounced differences in microstructure, regardless of if they had depression themselves.²¹ This sample’s strengths included direct clinical interviews for each generation of participants; a top-down approach of data collection, with prospective observation of the first generation, followed by the second and third generations, thereby limiting recall bias associated with recruiting the youngest generation and retrospectively collecting information on previous generations; and the collection of neural, genetic, and environmental data across multiple generations. But the relatively small, racially and culturally homogenous sample restricted generalizability afforded by large-scale studies.¹⁹

The second study, using the national Swedish medical registry,²⁰ also found that grandchildren with 2 previous generations affected by MDD had the highest risk of MDD themselves. However, the authors did not investigate other psychopathology. Thus, to our knowledge, grandchild outcomes beyond MDD have not been extended to a large, representative study.

Smaller family studies with detailed interview-based clinical phenotypes in each generation can identify the highest-risk groups for early intervention. However, they require replication in large samples to examine clinical and demographic variability. The advent of big population studies allows us to extend multigenerational studies to large, diverse samples. These big data studies are a welcome scientific asset but often have the drawback of less detailed, retrospective family history by participant self-report and might not be ideal for studying familial risk.²² However, if we can replicate clinical findings obtained in a relatively small sample with meticulous family history in a large population sample with less complete family data, this opens up opportunity to test neural findings underlying familial risk for psychopathology in big samples. Specifically, individuals with 2 prior generations affected who are at the highest risk of psychopathology^19,20 and neural abnormalities²¹ may be a more clinically homogenous group. Therefore, studying them could increase chances of identifying underlying mechanisms of psychopathology.

Here, by leveraging data from the Adolescent Brain Cognitive Development (ABCD) study,²³ a large representative sample of children aged 9 to 11 years, we aimed to extend findings from our high-risk study¹⁹ showing that offspring with 2 previous generations with depression are at highest risk of psychopathology. Second, we investigated whether these findings are similar across sex, race/ethnicity, and socioeconomic status (SES). We hypothesized increasing rates of psychopathology, with the lowest rates in children with no depression in the family, slightly higher rates in children with a grandparent with depression, higher rates in children with a parent with depression, and highest rates in children with both a parent and grandparent with depression and that this pattern would be robust across sociodemographic variables.

Methods

Data Source

Analyses were conducted using baseline data from the ABCD study²³ version 2.01 (July 2019), which included 11 875 children recruited from primary school and public school systems at 22 sites nationwide. Multistage probability sampling methods were used to maintain national representativeness in accordance with the American Community Survey and to reduce bias in statistically derived estimates.²⁴ The institutional review board of the University of California, San Diego gave centralized approval for the collection of the data and individual study sites where data were collected obtained approval from their local institutional review boards. All parents gave written informed consent and children verbal assent.

Procedures and Variables of Interest

Children and the reporter parents (9609 biological mother [85.7%]; 1123 biological father [9.8%]; 466 adoptive, custodial, or other parent [4.5%]) completed reports on children’s lifetime histories of psychiatric disorders. The self-administered computerized version of the Kiddie Schedule for Affective Disorders and Schizophrenia for DSM-5 (KSADS, Lifetime Version) was the primary mental health assessment instrument.^25,26 Additionally, parents completed reports on family history of psychiatric disorders, including MDD, and baseline demographic reports. See the eMethods in the Supplement for detailed description of ABCD study data files and variables.

Measures

Predictor: Family Risk

The participant’s parent reported on a history of depression in first-degree and second-degree relatives using the validated family history measure²⁷ used in the Collaborative Study on the Genetics of Alcoholism.²⁸ The question was, “Has ANY blood relative of your child ever suffered from depression, that is, have they felt so low for a period of at least two weeks that they hardly ate or slept or couldn't work or do whatever they usually do?” Using depressive histories from the 2 generations—grandparents (generation 1 [G1]) and parents (generation 2 [G2])—we formed a 4-category depression risk variable, reflecting how many prior generations were affected with depression: (1) neither G1 nor G2 (G1−/G2−; lowest risk assumed), (2) only G1 (G1+/G2−), (3) only G2 (G1−/G2+), and (4) both G1 and G2 (G1+/G2+; highest risk assumed).

Primary Outcome: Child Lifetime Prevalence of Psychiatric Disorders at Baseline (KSADS Interviews)

Nine psychiatric disorders or conditions were derived from DSM-5 diagnoses reported by both parents and children separately, using lifetime histories as baseline prevalence: MDD, any depressive disorder (including MDD, persistent depressive disorder [formerly dysthymic disorder], and depressive disorder not otherwise specified), social anxiety disorder (SAD), generalized anxiety disorder (GAD), any anxiety disorder (including GAD, SAD, and specific anxiety disorder not meeting criteria for GAD or SAD), bipolar disorder, sleep problems (diagnosis), suicidal behaviors (including active or passive ideation, plans/intention/preparation, and attempts), and any psychiatric disorder/condition. Eight additional diagnoses were derived from parent reports only: agoraphobia, simple/specific phobia, separation anxiety disorder, obsessive-compulsive disorder, posttraumatic stress disorder, attention-deficit hyperactivity disorder, conduct/oppositional defiant disorder, and psychotic disorders.

Potential Moderators

SES, child sex, and child race/ethnicity were examined as moderators of the association between familial risk and baseline prevalence of psychiatric conditions. We defined SES as a 3-category variable (low, medium, and high SES) derived from parental education and combined household income (eMethods in the Supplement). For child race/ethnicity, we selected the 3 largest racial/ethnic groups in the US: non-Hispanic White, non-Hispanic Black, and Hispanic. We collapsed other groups into a fourth category, other race/ethnicity, because of low individual numbers.

Potential Confounders

We controlled for child age, sexual orientation, religion, reporter relationship to child, parent’s age, gender identity, and marital status in the models (eMethods in the Supplement). SES, race/ethnicity, and sex were included as covariates for models in which they were not moderators. These variables were correlated with both familial risk and parent and/or child reports of 1 or more psychiatric disorders.

Statistical Analyses

Analyses were performed using SPSS version 27 (IBM). For descriptive analyses, χ² tests were used for categorical variables and t tests or analyses of variance for continuous variables, with Bonferroni adjustments for multiple comparisons. We compared included and excluded cases on demographic and clinical characteristics used in our regression models (eTable 1 in the Supplement). Parent and child reports were tested for concordance using Cohen κ measure of interrater reliability. Previous studies indicated that divergence of child and parent responses on psychiatric disorders warrant separate assessments of their reports.^29,30 Significance was set at a P value less than .05, and all P values were 2-tailed.

Association of Familial Risk With Prevalence of Psychiatric Disorders/Conditions

Generalized estimating equations (GEEs)³¹ were used to obtain the relative risks for the psychiatric diagnoses in children as reported by parents and children. GEE represents an extension of the general linear model approach, allowing for correlations among family members and site clusters. Data were modeled with Poisson distributions using the log-link function, controlling for potential confounders. The 4-level family risk variable was analyzed as a categorical variable, with children without a family history of depression as the reference group. Then, we examined the trend across the 4 categories using the Cochran-Armitage trend test,^32,33 testing increasing levels of risk. We evaluated separately the role of sex, SES, and race/ethnicity as moderators of the association of familial risk with psychiatric outcomes. We entered the main effect association(s) for risk and the moderating variable and the interaction between risk and moderating variable into the model. We used the ABCD study sampling weights in our GEE models and descriptive analyses. Development of the weighting scores is detailed in Garavan et al.²⁴

Additional and Post Hoc Analyses

To control for the possibility that the informant parent had depression and could therefore bias the reporting of the child’s, spouse’s, or parents’ depression,³⁴ we performed a sensitivity analysis removing any reporter parent who had depression themselves. Finally, we compared results from our analytic sample data with those from an imputed data set. Our missing data analysis showed a pattern consistent with missing at random. The expectation maximization method of multiple imputation^35,36 was used to generate complete data for family history and parent and child reports of KSADS diagnoses (eAppendix in the Supplement).

Results

Participants

The baseline ABCD sample comprised 11 875 children. Participants were excluded for missing data on family history (n = 420) or KSADS (n = 165 parent reports; n = 90 child reports), resulting in an analytic sample of 11 200 children from 9462 families. Among 11 200 included children, 5355 (47.8%) were female, and the mean (SD) age was 9.9 (0.6) years. Demographic characteristics of the analytic sample were distributed across the risk categories (Table 1) (eTable 1 in the Supplement).

Table 1. Demographic Characteristics of Sample by Risk Category.

Characteristic	Familial depression risk category, No. (%)^a^,^b				P value^c
Characteristic	G1−/G2−	G1+/G2−	G1−/G2+	G1+/G2+	P value^c
Total	6550 (58.2)	1480 (12.2)	1199 (11.3)	1971 (18.2)	NA
Female	3181 (49.4)	655 (46.1)	570 (48.1)	949 (49.2)	.03
Age, mean (SD), y
Child age	9.9 (0.6)	9.9 (0.6)	9.9 (0.6)	9.9 (0.6)	.41
Parent age	40.1 (6.9)	40.2 (6.1)	39.4 (6.7)	39.0 (6.7)	<.001
Race/ethnicity^d
Non-Hispanic White	3030 (45.0)	962 (65.8)	618 (53.2)	1223 (65.6)	<.001
Non-Hispanic Black	1181 (16.0)	91 (5.8)	208 (15.0)	195 (8.7)	<.001
Hispanic	1484 (26.9)	258 (20.9)	235 (23.2)	299 (17.0)	<.001
Other	848 (12.1)	167 (7.5)	134 (8.6)	252 (8.6)	.50
Parent’s marital status
Married	4474 (63.0)	1197 (75.6)	694 (51.6)	1249 (55.9)	<.001
Never married	859 (15.5)	82 (6.0)	175 (16.8)	232 (13.8)	<.001
Divorced/widowed/separated	755 (15.2)	144 (13.4)	249 (26.1)	346 (23.2)	.002
Living with partner	394 (6.3)	56 (4.0)	73 (5.5)	126 (7.0)	.002
Education and income, mean (SD)
Parental education level^e	17.0 (2.8)	17.8 (2.1)	16.9 (2.6)	17.2 (2.3)	<.001
Combined household income^f	7.2 (2.5)	8.0 (1.8)	6.8 (2.5)	7.1 (2.4)	<.001
SES^g
Low	2123 (40.3)	301 (28.0)	460 (46.3)	677 (42.8)	<.001
Medium	3161 (44.2)	847 (54.4)	541 (41.4)	987 (44.6)	<.001
High	1204 (15.6)	331 (17.6)	192 (12.3)	300 (12.6)	<.001
Informant’s relationship to child
Biological mother	5509 (83.8)	1320 (89.4)	1024 (84.8)	1756 (89.7)	<.001
Biological father	722 (10.9)	138 (8.8)	123 (10.9)	140 (6.3)	<.001
Adoptive/custodial/other parent	317 (5.3)	22 (1.8)	52 (4.3)	75 (4.0)	<.001
Born outside the US
Child	268 (5.3)	34 (2.8)	20 (2.3)	15 (0.7)	<.001
Parent/grandparent	2367 (38.1)	421 (28.1)	335 (30.0)	487 (22.8)	<.001
Sexual orientation
Parent report
Yes	4 (0.1)	0	0	0	NA
Maybe	352 (4.9)	123 (7.6)	112 (8.1)	258 (12.9)	<.001
Child report
Yes	16 (0.2)	1 (0)	2 (0.3)	19 (1.0)	.001
Maybe	51 (0.9)	18 (1.2)	12 (1.2)	23 (1.1)	.61
Religious preference
Denominational	4650 (76.2)	1043 (74.7)	809 (71.7)	131 (72.1)	<.001
Nondenominational	1362 (21.1)	317 (20.5)	254 (23.0)	452 (22.4)	.30
Agnostic/atheist	208 (2.7)	81 (4.8)	69 (5.3)	108 (5.5)	<.001

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Abbreviations: G1, generation 1 (grandparents); G2, generation 2 (parents); NA, not applicable; SES, socioeconomic status.

^{^a}

Children were grouped into 4 risk categories, reflecting how many prior generations were affected with depression: (1) neither G1 nor G2 (G1−/G2−), (2) only G1 (G1+/G2−), (3) only G2 (G1−/G2+), and (4) both G1 and G2 (G1+/G2+).

^{^b}

Values presented are unweighted counts and weighted percentages within each depression risk categories.

^{^c}

Differences in prevalence among risk categories were calculated using χ² tests for categorical variables and one-way analysis of variance for continuous variables, with Bonferroni adjustments used for multiple comparisons.

^{^d}

We selected the 3 largest racial/ethnic groups in the US: non-Hispanic White, non-Hispanic Black, and Hispanic. We collapsed other groups into other race/ethnicity because of low individual numbers.

^{^e}

Created using the highest grade or degree completed, using the following values: 0, never attended school/kindergarten only; 1, 1st grade; 2, 2nd grade; 3, 3rd grade; 4, 4th grade; 5, 5th grade; 6, 6th grade; 7, 7th grade; 8, 8th grade; 9, 9th grade; 10, 10th grade; 11, 11th grade; 12, 12th grade, no diploma; 13, high school graduate; 14, GED or equivalent diploma; 15, college credit/postsecondary education, no degree; 16, associate’s degree: occupational, technical, or vocational degree; 17, associate’s degree: academic program; 18, bachelor’s degree; 19, master’s degree; 20, professional school degree (eg, MD, DDS, DVN, JD); 21, doctoral degree (eg, PhD, EdD).

^{^f}

Created using combined household income in the past 12 months before taxes, using the following values: 1, <$5000; 2, $5000-$11 999; 3, $12 000-$15 999; 4, $16 000-$24 999; 5, $25 000-$34 999; 6, $35 000-$49 999; 7, $50 000-$74 999; 8, $75 000-$99 999; 9, $100 000-$199 999; 10, ≥$200 000.

^{^g}

For SES threshold definitions, see the eMethods in the Supplement.

Prevalence of Clinical Diagnoses by Familial Risk Category

There was low agreement between parent and child reports (κ estimates ranged from 0.03 to 0.20; eTable 2 in the Supplement). Consequently, we present results for parent and child reports separately. As reported by parents, higher prevalence of psychiatric disorders was observed with increasing levels of familial risk as confirmed by increasing point estimates across risk categories and significant trend statistics for almost all evaluated disorders (Figure 1) (Table 2). By parent reports, the weighted prevalence of any depressive disorder among children was 3.8% (95% CI, 3.2-4.3) for G1−/G2− children, 5.5% (95% CI, 4.3-7.1) for G1+/G2− children, 10.4% (95% CI, 8.6-12.6) for G1−/G2+ children, and 13.3% (95% CI, 11.6-15.2) for G1+/G2+ children (Cochran-Armitage trend = 243.77; P < .001). The weighted suicidal behavior prevalence among children was 5.0% (95% CI, 4.5-5.6) for G1−/G2− children, 7.2% (95% CI, 5.8-8.9) for G1+/G2− children, 12.1% (95% CI, 10.1-14.4) for G1−/G2+ children, and 15.0% (95% CI, 13.2-17.0) for G1+/G2+ children (Cochran-Armitage trend = 188.66; P < .001). The weighted prevalence of MDD was 1.2% (95% CI, 1.0-1.6) among G1−/G2− children, 2.3% (95% CI, 1.5-3.4) among G1+/G2− children, 4.9% (95% CI, 3.6-6.6) among G1−/G2+ children, and 7.4% (95% CI, 6.2-8.8) among G1+/G2+ children (Cochran-Armitage trend = 202.29; P < .001). This trend was similar for SAD, GAD, any anxiety disorder, sleep problem, and any disorder as reported by the parent (Table 2). When reported by the child, G1+/G2+ children had highest prevalence rates except for MDD and any anxiety disorder (Table 2). By child reports, the weighted prevalence of depressive disorder was 4.8% (95% CI, 4.3-5.5) for G1−/G2− children, 4.3% (95% CI, 3.2-5.7) for G1+/G2− children, 6.3% (95% CI, 4.9-8.1) for G1−/G2+ children, and 7.0% (95% CI, 5.8-8.5) for G1+/G2+ children (Cochran-Armitage trend = 9.01; P = .002), and the weighted prevalence of suicidal behaviors was 7.4% (95% CI, 6.7-8.2) for G1−/G2− children, 7.0% (95% CI, 5.6-8.6) for G1+/G2− children, 9.8% (95% CI, 8.1-12.0) for G1−/G2+ children, and 13.8% (95% CI, 12.1-15.8) for G1+/G2+ children (Cochran-Armitage trend = 46.69; P < .001).

Figure 1. — Children were grouped into 4 risk categories, reflecting how many prior generations were affected with depression: (1) neither grandparents (generation 1 [G1]) nor parents (generation 2 [G2]; G1−/G2−), (2) only G1 (G1+/G2−), (3) only G2 (G1−/G2+), and (4) both G1 and G2 (G1+/G2+). Error bars indicate 95% CIs.

Table 2. Prevalence Trends for Psychological Disorders Based on Parent and Child Reports on Kiddie Schedule for Affective Disorders and Schizophrenia for DSM-5 Across Levels of Familial Depression Risk.

Disorder	Familial depression risk category, weighted % (95% CI)^a^,^b				Cochran-Armitage Trend
Disorder	G1−/G2−	G1+/G2−	G1−/G2+	G1+/G2+	Cochran-Armitage Trend
Parent report
Major depressive disorder	1.2 (1.0-1.6)	2.3 (1.5-3.4)	4.9 (3.6-6.6)	7.4 (6.2-8.9)	202.29^c
Any depressive disorder^d	3.8 (3.2-4.3)	5.5 (4.3-7.1)	10.4 (8.6-12.6)	13.3 (11.6-15.2)	243.77^c
Social anxiety disorder	3.4 (2.9-3.9)	5.0 (3.9-6.4)	5.8 (4.5-7.5)	8.0 (6.8-9.5)	102.77^c
Generalized anxiety disorder	2.4 (2.0-2.9)	3.6 (2.8-4.8)	5.5 (4.2-7.1)	12.1 (10.5-14.1)	229.83^c
Any anxiety disorder^e	7.0 (6.3-7.8)	10.0 (8.4-11.9)	13.0 (11.0-15.3)	21.1 (19.0-23.3)	289.84^c
Bipolar disorders^f	5.7 (5.1-6.4)	4.8 (3.7-6.3)	11.5 (9.6-13.9)	11.2 (9.5-12.8)	61.21^c
Sleep problem (diagnosis)	7.2 (6.5-8.0)	10.3 (8.7-12.2)	11.8 (9.8-14.2)	16.7 (14.9-18.7)	151.23^c
Suicidal behaviors^g	5.0 (4.5-5.6)	7.2 (5.8-8.9)	12.1 (10.1-14.4)	15.0 (13.2-17.0)	188.66^c
Any disorder/condition^h	21.0 (19.9-22.2)	26.1 (23.6-28.7)	36.8 (33.7-40.1)	43.9 (41.4-46.5)	413.66^c
Child report
Major depressive disorder	2.7 (2.2-3.2)	2.1 (1.4-3.1)	3.9 (2.8-5.4)	3.8 (2.9-5.0)	2.34
Any depressive disorder^d	4.8 (4.3-5.5)	4.3 (3.2-5.7)	6.3 (4.9-8.1)	7.0 (5.8-8.5)	9.01ⁱ
Social anxiety disorder	0.6 (0.4-0.8)	0.8 (0.3-1.6)	1.3 (0.7-2.2)	1.6 (1.1-2.5)	16.62^c
Generalized anxiety disorder	0.5 (0.3-0.7)	0.5 (0.3-1.1)	0.9 (0.4-1.8)	1.5 (1.0-2.4)	13.33^c
Any anxiety disorder^e	2.7 (2.3-3.2)	3.3 (2.6-4.8)	5.1 (3.7-7.0)	4.6 (3.7-6.6)	19.15^c
Bipolar disorders^f	0.8 (0.6-1.1)	1.2 (0.7-2.2)	0.9 (0.4-1.9)	1.3 (0.8-2.1)	0.57
Sleep problem (diagnosis)	14.8 (13.8-15.8)	15.1 (13.2-17.3)	17.1 (14.7-19.8)	18.4 (16.5-20.6)	10.91ⁱ
Suicidal behaviors^g	7.4 (6.7-8.2)	7.0 (5.6-8.6)	9.8 (8.1-12.0)	13.8 (12.1-15.8)	46.69^c
Any disorder/condition^h	23.0 (21.9-24.3)	22.4 (20.1-25.0)	28.0 (25.2-31.2)	31.0 (28.8-33.6)	39.07^c

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Abbreviations: G1, generation 1 (grandparents); G2, generation 2 (parents).

^{^a}

^{^b}

Baseline prevalence was obtained from generalized estimating equations linear models and was adjusted for child characteristics (sex, age, race/ethnicity, sexual orientation, religious preference, and relationship to informant) and parents characteristics (age, marital status, and socioeconomic status based on combined household income and educational level).

^{^c}

P < .001.

^{^d}

Any depressive disorder includes one of major depressive disorder, persistent depressive disorder, or depressive disorder not otherwise specified.

^{^e}

Any anxiety disorder includes one of social anxiety disorder, generalized anxiety disorder, or anxiety disorder not meeting impairment criteria for social or generalized anxiety disorders.

^{^f}

Bipolar disorders include bipolar disorders 1 and 2 and bipolar disorders not otherwise specified.

^{^g}

Suicidal behaviors include suicidal ideation (passive or active), suicidal plans, and suicide attempts.

^{^h}

Any disorder/condition refers to one or more of the 8 previously listed disorders/behaviors or conditions.

^ⁱ

P < .01.

According to parents, G1+/G2+ children were 6.0-fold more likely to have MDD and 2.1-fold more likely to have any disorder compared with G1−/G2− children (eTable 3 in the Supplement). KSADS diagnoses only reported by the parent showed a similar trend, with significant trend statistics of higher rates by increasing familial risk (eTable 4 in the Supplement).

Moderation by Sociodemographic Variables

To investigate whether the associations between family risk and diagnoses were moderated by sociodemographic variables, we tested main and interaction statistical effects of sex, race/ethnicity, and SES for depressive disorders, anxiety disorders, suicidal behaviors, and any disorder/condition (Table 3; Figure 2) (eTables 5 and 6 in the Supplement).

Table 3. Moderation (Interaction) Associations of Sex, Socioeconomic Status (SES), and Race/Ethnicity and Familial Depression of Risk on Psychiatric Disorders.

Interaction	Psychiatric condition/disorder
Interaction	Depressive disorders	Anxiety disorders	Suicidal ideation/behaviors	Any psychiatric disorder/condition
Parent reports
Sex^a	χ²₁ = 2.3	χ²₁ = 0	χ²₁ = 40.8^b	χ²₁ = 14.6^b
Sex × risk^c	χ²₃ = 3.3	χ²₃ = 1.2	χ²₃ = 2.3	χ²₃ = 4.8
SES^a	χ²₂ = 38.9^d	χ²₂ = 7.8	χ²₂ = 3.0	χ²₂ = 9.9
SES × risk^c	χ²₆ = 16.4^b	χ²₆ = 16.2^b	χ²₆ = 8.3	χ²₆ = 10.7^e
Race/ethnicity^a	χ²₃ = 13.5^f	χ²₃ = 16.0^f	χ²₃ = 6.1	χ²₃ = 2.7
Race/ethnicity × risk^c	χ²₉ = 7.1	χ²₉ = 18.8^b	χ²₉ = 10.2	χ²₉ = 16.4^e
Child reports
Sex^a	χ²₁ = 0.8	χ²₁ = 0.8	χ²₁ = 2.9^e	χ²₁ = 2.8^e
Sex × risk^c	χ²₃ = 6.0	χ²₃ = 2.1	χ²₃ = 2.1	χ²₃ = 0.8
SES^a	χ²₂ = 15.0^f	χ²₂ = 2.2	χ²₂ = 0.6	χ²₂ = 11.6^f
SES × risk^c	χ²₆ = 1.9	χ²₆ = 4.1	χ²₆ = 1.7	χ²₆ = 0.4
Race/ethnicity^a	χ²₃ = 33.4^d	χ²₃ = 5.2	χ²₃ = 3.1	χ²₃ = 15.1^f
Race/ethnicity × risk^c	χ²₉ = 16.8^e	χ²₉ = 5.4	χ²₉ = 5.5	χ²₉ = 2.3

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^{^a}

Main effect associations for moderator variable; 2-tailed tests of significance. All χ² estimates obtained through generalized estimating equation analyses.

^{^b}

P < .05.

^{^c}

Moderation (interaction) associations between moderator variable and familial depression risk; 2-tailed tests of significance.

^{^d}

P < .001.

^{^e}

P < .10.

^{^f}

P < .01.

Figure 2. — Children were grouped into 4 risk categories, reflecting how many prior generations were affected with depression: (1) neither grandparents (generation 1 [G1]) nor parents (generation 2 [G2]; G1−/G2−), (2) only G1 (G1+/G2−), (3) only G2 (G1−/G2+), and (4) both G1 and G2 (G1+/G2+). A, By parent report, rates of any psychiatric disorder were lower in girls than boys, but both sexes showed increasing prevalence with increasing familial risk. B, By child report, sex did not moderate children’s prevalence rates. C, By parent report, SES did not moderate children’s prevalence rates. D, By child report, children in the low SES category had higher rates of any disorder than those in the medium or high SES categories, but there was no moderating effect of SES by familial risk. E, By parent report, race/ethnicity did not moderate children’s prevalence rates. F, By child report, Black children had higher rates of any disorder than White or Hispanic children, but there was no moderating effect of race/ethnicity by familial risk. The other race/ethnicity group was created because of low individual numbers. Error bars indicate 95% CIs.

^aP < .05.

Parent Reports

Rates of any depressive disorder and any anxiety disorder were similar between girls and boys. Boys had higher rates of suicidal behaviors (mean, 11.4%; SE, 0.6) and any disorder (mean, 32.9%; SE, 0.8) than girls (suicidal behavior: mean, 6.3%; SE, 0.5; any disorder: mean, 28.3%; SE, 0.9) (Figure 2A) (eTable 5 in the Supplement). There was no family risk by sex moderation for these diagnoses, indicating that prevalence increased similarly with higher family risk across sex.

Children in the low SES category had higher rates of any depressive disorder (mean, 10.1%; SE, 0.7) compared with those in the medium SES (mean, 5.4%; SE, 0.7) and high SES (mean, 5.7%; SE, 0.4) categories (Figure 2C) (eTable 5 in the Supplement). A significant family risk by SES interaction for depressive disorders (χ²₆ = 16.4; P = .01) and anxiety disorders (χ²₆ = 16.2; P = .01) shows that rates in children in the low and medium SES categories increased with family risk, while rates in the high SES category did not (eTable 6 in the Supplement). SES did not moderate associations between family risk and suicidal behaviors or any disorder, indicating that higher family risk corresponded to higher prevalence similarly across SES.

Hispanic children had higher rates of any depressive disorder (mean, 9.1%; SE, 0.9) than White children (mean, 6.5%; SE, 0.4) or children of other races/ethnicities (mean, 5.6%; SE, 0.8) (Figure 2E). White children had higher rates of anxiety disorder (mean, 13.1%; SE, 0.6) compared with Hispanic children (mean, 10.2%; SE, 0.9) and children of other races/ethnicities (mean, 8.7%; SE, 1.1). Race/ethnicity moderated the association between family risk and anxiety disorders (χ²₉ = 18.8; P = .03). Rates of anxiety increased with increasing family risk for White, Black, and Hispanic children, but White and Hispanic G1+/G2+ children had especially high rates of MDD (eTable 6 in the Supplement). There were no race/ethnicity main or moderation associations with suicidal behaviors or any disorder.

Child Reports

Depressive disorder, anxiety disorder, suicidal behaviors, and any disorder rates reported by the children did not differ by sex (Figure 2B). Prevalence was higher in children in the low SES category compared with those in the medium and high SES categories for depressive disorders (χ²₂ = 15.0; P = .001) and any disorder (χ²₂ = 11.6; P = .003) (Figure 2D) (eTable 5 in the Supplement). Depressive disorders were more prevalent in Black children and children of other races/ethnicities, and any disorder was more prevalent in Black children compared with White and Hispanic children (Figure 2F) (eTable 5 in the Supplement). There were no moderation effects of sex, SES, or race/ethnicity, indicating family risk increased rates of disorders similarly across sociodemographic characteristics.

Discussion

We determined whether the association of 2 prior generations of family depression with grandchildren’s psychopathology, established in family studies, could be reliably demonstrated in a larger and representative data set with informant-reported family histories. As hypothesized, we found higher prevalences of psychiatric disorders with increasing family risk in prepubescent children across sociodemographic characteristics. Specifically, children with both a parent and a grandparent with depression had higher rates of psychiatric disorders compared with children with only a parent with depression, who had higher rates compared with children with only a grandparent with depression, who had higher rates than children with no familial history of depression. This pattern was generally observed across sex, SES, and race/ethnicity, although there were some variations within SES and racial/ethnic groups. Our risk patterns are consistent with an additive rather than multiplicative model,³⁷ similar to additive risk effects on children when 1 vs 2 parents are affected by depression or anxiety.³⁸

These results extend our earlier findings^19,39 to a representative population of US children. The high-risk study¹⁹ also found increased rates of any psychiatric disorders in children with at least 1 grandparent and parent diagnosed with depression compared with just 1 or no prior generations with depression (42 of 71 [59.2%] after first 2 waves with mean age of 12 years³⁹ and 27 of 38 [71%] at a next wave with mean [SD] age of 18.2 [7.3] years¹⁹). The rates in the high-risk study are higher than in this study (43.9% as reported by parents), which is likely attributable to participants’ older mean age in the high-risk study.¹⁹ The current results suggest that having a grandparent with depression confers lower risk of a psychiatric disorder among children than having a parent with depression, a difference we predict will become more pronounced as the children grow older. The high-risk study¹⁹ used a clinician-based KSADS interview and direct family interviews, while the ABCD study used a computerized self-administered KSADS and family history reports. The similarity between the findings from both cohorts show that a bottom-up approach with a family history assessment, with one relative reporting on others, may be a feasible and faster way to study multiple generations than using direct interviews starting with the first generation and waiting for the subsequent generations to age in.

A 2019 study of a register-based Swedish cohort of more than 400 000 mothers and grandmothers also found that grandchildren with 2 previous generations of maternal depression had the highest rates of MDD.²⁰ Other disorders were not reported. Our results extend that study by showing that grandchildren with 2 previous generations affected had highest prevalences for a range of psychiatric diagnoses and across sociodemographic characteristics. Lastly, Pettit and colleagues⁴⁰ did not assess prevalence rates but found that a parent and grandparent with MDD predicted higher mean Child Behavior Checklist internalizing and anxious depressed scores in children (mean [SD] age, 4.7 [2.5] years) compared with those with only a grandparent or parent with MDD, further establishing a family risk effect.

The mechanisms by which having multiple generations of family with depression increases risk of psychiatric disorders in offspring remain a topic of scientific and clinical interest. MDD is moderately heritable,⁴¹ and having multiple generations affected could indicate higher genetic loadings for psychopathology. Additionally, perinatal and postnatal effects,⁴² parenting styles,⁴³ and higher stress in families with depression⁴⁴ can have effects through the hypothalamic-pituitary-adrenal axis, epigenetic mechanisms, and inflammatory pathways in offspring.^45,46 For example, Hammen and colleagues⁴⁷ proposed an interpersonal stress model showing an interaction of G1 and G2 depression with parenting and other social factors, which yielded direct and indirect effects on child depression. Furthermore, microstructure in the dentate gyrus of the hippocampus, important for resilience to stress and depression, differed most in offspring with 2 generations compared with 1 and no prior generations of depression.²¹

Studies such as the ABCD study provide access to large samples of magnetic resonance imaging and other biological data. Our findings suggest that third-generation offspring with 2 prior generations affected by depression may define a clinically more homogenous subgroup for studies of biological mechanisms of psychopathology. The fact that the findings cut across diverse groups makes them even more robust. A parental depression effect on subcortical volume in offspring has already been established,¹⁴ and in the future, we aim to study the effects of 2 generations affected on offspring structural and functional neural markers.

Our findings have clinical implications. Screening tools with simple questions on family history could be a valuable addition to pediatric and other clinical care. Familial depression can have a long-term and debilitating clinical course.^3,19 Early identification and intervention may break the cycle of transmission or at least the consequences of untreated symptoms.

Limitations

Our study has limitations. First, the ABCD study relies on family history reports from one informant instead of direct interviews with family members. Relying on informant-based histories is common in large data sets but could lead to bias from reporters who themselves have psychopathology. However, our results suggest that this method reasonably approximated results from studies with individual-based assessments, and our sensitivity analyses confirmed that effects were not due to reporter parent depression.

Second, the parent-child discrepancy we observed in KSADS diagnoses is similar to that of other studies comparing parent and child reports.⁴⁸ However, in contrast to this study, previous studies found that parents underreported their children’s symptoms.²⁹ Our sensitivity analyses did not support overwhelming bias on the part of the parents with depression. Still, this discrepancy warrants tentative interpretation and future replication of the moderation results and further inquiry as to the nature of divergent reports. Depression often manifests in adolescence, and the current sample is relatively young. Rates will likely increase in follow-up ABCD study waves. Nonetheless, seeing high rates at this young age indicates the strength of multiple generations of depression as a risk factor.

Third, we analyzed child-reported and parent-reported diagnoses separately, since the concordance between children and parents was not high. The validating study of the computerized self-report version of the KSADS showed that using algorithms to integrate parent and child report data more closely approximated clinician-derived diagnoses based on interviews with both informants.²⁶ Unfortunately, these integration algorithms are not yet available for the ABCD study. Future refinement of these algorithms could assist with subsequent studies.

Conclusions

These findings validate the reciprocal and complementary nature of big data and family studies in psychiatric epidemiology.²² We demonstrate that the well-established family risk across generations derived from family studies can be mapped on to a larger, diverse study using a time-efficient family history approach and that these effects are generalizable across racial/ethnic groups, sex, and SES categories. The results increase evidence that family history should be interrogated in clinical settings given the often chronic and debilitating outcomes of childhood onset of psychopathology^49,50,51,52 and the opportunity for early interventions. The findings also suggest that family history is an important moderator defining a clinically homogenous subgroup at high risk, which may be reliably used to study underlying mechanisms in studies such as the ABCD study that have access to large samples of magnetic resonance imaging and other biological data.

Supplement.

eMethods. Main measures and ABCD study data files.

eTable 1. Demographic and clinical characteristics of study sample with comparisons between included and excluded cases.

eTable 2. Correlation between parent and child reports on KSADS diagnoses.

eTable 3. Relative risks of G3 KSADS diagnoses by familial risk.

eTable 4. Prevalence of psychiatric disorders that were only reported by a parent across levels of familial depression risk.

eTable 5. Main effects of sex, SES, and race/ethnicity as reported by parents and children.

eTable 6. Moderation effects of sex, SES, and race/ethnicity on the influence of familial depression risk on psychiatric outcomes as reported by parents.

eAppendix. Sensitivity analysis and imputed data.

Click here for additional data file.^{(345KB, pdf)}

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42.Sawyer KM, Zunszain PA, Dazzan P, Pariante CM. Intergenerational transmission of depression: clinical observations and molecular mechanisms. Mol Psychiatry. 2019;24(8):1157-1177. doi: 10.1038/s41380-018-0265-4 [DOI] [PubMed] [Google Scholar]
43.Lovejoy MC, Graczyk PA, O’Hare E, Neuman G. Maternal depression and parenting behavior: a meta-analytic review. Clin Psychol Rev. 2000;20(5):561-592. doi: 10.1016/S0272-7358(98)00100-7 [DOI] [PubMed] [Google Scholar]
44.Gershon A, Hayward C, Schraedley-Desmond P, Rudolph KD, Booster GD, Gotlib IH. Life stress and first onset of psychiatric disorders in daughters of depressed mothers. J Psychiatr Res. 2011;45(7):855-862. doi: 10.1016/j.jpsychires.2011.03.016 [DOI] [PMC free article] [PubMed] [Google Scholar]
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47.Hammen C, Shih JH, Brennan PA. Intergenerational transmission of depression: test of an interpersonal stress model in a community sample. J Consult Clin Psychol. 2004;72(3):511-522. doi: 10.1037/0022-006X.72.3.511 [DOI] [PubMed] [Google Scholar]
48.Grills AE, Ollendick TH. Multiple informant agreement and the anxiety disorders interview schedule for parents and children. J Am Acad Child Adolesc Psychiatry. 2003;42(1):30-40. doi: 10.1097/00004583-200301000-00008 [DOI] [PubMed] [Google Scholar]
49.Fernando K, Carter JD, Frampton CMA, et al. Childhood-, teenage-, and adult-onset depression: diagnostic and individual characteristics in a clinical sample. Compr Psychiatry. 2011;52(6):623-629. doi: 10.1016/j.comppsych.2010.12.006 [DOI] [PubMed] [Google Scholar]
50.Gollan J, Raffety B, Gortner E, Dobson K. Course profiles of early- and adult-onset depression. J Affect Disord. 2005;86(1):81-86. doi: 10.1016/j.jad.2004.12.009 [DOI] [PubMed] [Google Scholar]
51.Klein DN, Schatzberg AF, McCullough JP, et al. Early- versus late-onset dythymic disorder: comparison in out-patients with superimposed major depressive episodes. J Affect Disord. 1999;52(1-3):187-196. doi: 10.1016/S0165-0327(98)00079-2 [DOI] [PubMed] [Google Scholar]
52.Parker G, Roy K, Hadzi-Pavlovic D, Mitchell P, Wilhelm K. Distinguishing early and late onset non-melancholic unipolar depression. J Affect Disord. 2003;74(2):131-138. doi: 10.1016/S0165-0327(02)00002-2 [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplement.

eMethods. Main measures and ABCD study data files.

eTable 1. Demographic and clinical characteristics of study sample with comparisons between included and excluded cases.

eTable 2. Correlation between parent and child reports on KSADS diagnoses.

eTable 3. Relative risks of G3 KSADS diagnoses by familial risk.

eTable 4. Prevalence of psychiatric disorders that were only reported by a parent across levels of familial depression risk.

eTable 5. Main effects of sex, SES, and race/ethnicity as reported by parents and children.

eTable 6. Moderation effects of sex, SES, and race/ethnicity on the influence of familial depression risk on psychiatric outcomes as reported by parents.

eAppendix. Sensitivity analysis and imputed data.

Click here for additional data file.^{(345KB, pdf)}

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PERMALINK

Association of Multigenerational Family History of Depression With Lifetime Depressive and Other Psychiatric Disorders in Children

Milenna T van Dijk, PhD

Eleanor Murphy, PhD

Jonathan E Posner, MD

Ardesheer Talati, PhD

Myrna M Weissman, PhD

Key Points

Question

Findings

Meaning

Abstract

Importance

Objective

Design, Setting, and Participants

Main Outcomes and Measures

Results

Conclusions and Relevance

Introduction

Methods

Data Source

Procedures and Variables of Interest

Measures

Predictor: Family Risk

Primary Outcome: Child Lifetime Prevalence of Psychiatric Disorders at Baseline (KSADS Interviews)

Potential Moderators

Potential Confounders

Statistical Analyses

Association of Familial Risk With Prevalence of Psychiatric Disorders/Conditions

Additional and Post Hoc Analyses

Results

Participants

Table 1. Demographic Characteristics of Sample by Risk Category.

Prevalence of Clinical Diagnoses by Familial Risk Category

Figure 1. Prevalence of Psychiatric Disorders in Children by Familial Depression Risk Reported by Parents and Children.

Table 2. Prevalence Trends for Psychological Disorders Based on Parent and Child Reports on Kiddie Schedule for Affective Disorders and Schizophrenia for DSM-5 Across Levels of Familial Depression Risk.

Moderation by Sociodemographic Variables

Table 3. Moderation (Interaction) Associations of Sex, Socioeconomic Status (SES), and Race/Ethnicity and Familial Depression of Risk on Psychiatric Disorders.

Figure 2. Prevalence of Any Psychiatric Disorder in Children by Familial Depression Risk by Sex, Socioeconomic Status (SES), and Race/Ethnicity Reported by Parents and Children.

Parent Reports

Child Reports

Discussion

Limitations

Conclusions

References

Associated Data

Supplementary Materials

ACTIONS

PERMALINK

RESOURCES

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