Video Abstract
The nature and magnitude of the cognitive and mental health risks among the offspring of young mothers is not fully understood. Our objective is to examine the risk of mental disorders in these offspring.
Five databases (Medline, Embase, Web of Science, PsycINFO, and CINAHL) were searched from their inceptions until February 2022. Studies were eligible if they assessed offspring of young mothers (<21 years), contained a control group, and assessed any cognitive and/or mental health outcomes. Random-effects meta-analysis was used to generate standardized mean differences (SMDs) in infants (0–3 years), children (4–9), adolescents (10–19), and adults (20+). Methodological bias was assessed using the Newcastle-Ottawa Scale.
51 outcomes were meta-analyzed. Levels of cognitive and learning problems were higher among the infants (SMD = 0.30 [95% confidence interval 0.0–0.55]) and adolescents (SMD = 0.43 [0.24 to 0.62]) of young mothers. Adolescents had more symptoms of delinquency (SMD = 0.24 [0.12 to 0.36]). As adults, they are more often convicted of violent crimes (SMD = 0.36 [0.22 to 0.50]). Internalizing symptoms were higher in these offspring in childhood (SMD = 0.29 [0.14 to 0.45]) and adulthood (SMD = 0.35 [0.34 to 0.36]). This review uses unadjusted data and is thus unequipped to infer causality. Studies have high attrition and rely heavily on self-report.
Young mothers’ offspring have more cognitive, externalizing, and internalizing problems across the lifespan than individuals born to mothers ≥21 years of age. They may benefit from early detection and support.
Pregnancy during adolescence and emerging adulthood can have a significant impact on mothers and their offspring. Raising a child is challenging for young mothers as they experience more socioeconomic disadvantages and mental health problems.1,2 Even if these risks are not present before pregnancy, childrearing can introduce new obstacles.3 Young mothers can discontinue their education and so, may experience additional financial hardship in the short- and long-term.4 As outlined in the Family Stress Model, caring for a child in the context of resource constraints can contribute to mental distress in young mothers that impairs their ability to parent and negatively impacts their children’s wellbeing.5–7
The offspring of young mothers can experience difficulties at multiple developmental stages. As early as kindergarten, they can perform more poorly in reading and math.8 In adolescence, they interact with the justice system more frequently9,10 and engage in more risky sexual behavior,11 experiences that can perpetuate an intergenerational risk cycle.12
Although young mothers’ offspring have been the subject of substantial research, there are still gaps in our understanding of the problems they face, the magnitude of these risks, and when they first emerge. Few studies have examined the early development (eg, infancy) of these offspring,13,14 and predictors of future life difficulties in areas such as mental health and social development have been relatively neglected.15,16 Most research examines adolescent outcomes,17,18 though the magnitude of risk estimates vary between studies and rely heavily on self-report data.19,20 A systematic review suggested offspring externalizing risk is increased, but it pooled across ages and failed to present stage-specific estimates.21 In the absence of data from longer-term cohort studies or syntheses of other outcomes of interest, it is difficult to draw externally valid conclusions about the cognitive functioning and mental health of these offspring.
A contemporary systematic review that addresses existing knowledge gaps is needed to provide accurate estimates of the magnitude and developmental timing of these risks. Nearly 17 million adolescents worldwide give birth each year, and the difficulties their offspring face are a significant public health issue given their burden of suffering and costs for healthcare, education, and social services.22
Methods
Identification and Selection of Studies
The protocol guiding this review was registered with PROSPERO (August 3, 2020; CRD42020152026). A systematic search of 5 databases (Medline, Embase, Web of Science, PsycINFO, and CINAHL) from their inceptions until February 2022 was conducted, including abstracts and gray literature. This was created in collaboration with a health sciences librarian and included terms for adolescent pregnancy combined with cognitive and mental health outcomes (Supplemental Figs 3A–3E).
Studies were selected if they included offspring born to a young mother (<21 years at delivery), included a control group of offspring born to mothers ≥21,23 and assessed cognitive, externalizing, and/or internalizing mental health outcomes. Twenty one years of age was set as the cut point to capture the oldest definition of young or teenage childbearing found during a preliminary scan of the literature. Studies were excluded if they involved an intervention or if they were not available in English, as resource constraints did not permit translation. Studies were further restricted to those originating from Western countries, as young childbearing differs in non-Western and Western countries.24 Cognitive outcomes included all those relating to cognitive functioning, learning and educational attainment. Externalizing was defined as any of conduct disorder, delinquency, and/or other behavioral problems; attention deficit/hyperactivity disorder (ADHD) or hyperactivity; substance misuse; and violent and nonviolent criminal convictions. Internalizing grouped depression, anxiety, suicidal ideation, psychotic disorders, and any other general measures of psychological functioning and mental health. Four independent reviewers (L.C., M.F., C.L., Z.T.) screened titles and abstracts and conducted full-text review. The ancestry approach identified studies not located by our search.
Data Extraction and Quality Assessment
A data extraction template was pilot tested by 4 independent reviewers (L.C., M.F., C.L., Z.T.) on 5 randomly selected studies. The result was a standardized extraction form that included information on study design, duration, measurement occasion(s), and study eligibility criteria; study objectives; sample size; and maternal and offspring characteristics, outcomes and measures, covariates, and study outcomes. If any data were missing, we contacted its lead, second, or senior authors by e-mail. The extraction form also extracted risk of bias using the Newcastle-Ottawa scales for cohort, case control, and cross-sectional studies.25,26 These scales rank selection bias, between-group comparability, and exposure in outcome ascertainment, and score cohort and case control studies out of 9 stars and cross-sectional studies out of 10. A lower number of stars indicates a higher risk of bias. Disagreements that arose during the data extraction and bias assessments were again reviewed and resolved by the senior author (R.V.).
Meta-Analyses
Offspring outcomes were examined in 4 separate developmental stages: infancy (0–3 years), childhood (4–9 years), adolescence (10–19 years), and adulthood (20+ years).27,28 Studies were included in meta-analyses if they assessed an outcome in the same category as another study (judged according to our a priori criteria) within the same offspring age group. The minimum number of studies per meta-analysis was set as 2, provided they were meaningfully similar with respect to sample characteristics and outcome measurement. This threshold was chosen in the interest of providing the most complete age-specific estimates within all outcomes, acknowledging that our age-stratified approach led to a small number of studies in some categories.
Meta-analyses were conducted using a random-effects model in RevMan 5.3 to produce standardized mean differences (SMD) with 95% confidence intervals (CIs) for each outcome. Where dichotomous data were reported, odds ratios were converted to SMDs with CIs.29 95% CIs were converted to standard errors, so the generic inverse variance outcome type could be used to generate forest plots.29 I2 tests were used to assess heterogeneity. Egger’s publication bias test was planned for meta-analyses with >10 studies. For analyses with fewer studies, funnel plots were visually inspected.30
Results
After removing duplicate records, 4318 titles and abstracts were screened (κ = .96). 140 full-text articles were assessed and 28 were included.17–20,23,31–53 The manuscript from Zimmerman et al contained 2 studies and both were included separately.54 The ancestry approach identified 6 additional studies,54–59 bringing the total to 35 (Fig 1).
Seventy-five outcomes were extracted and 51 were eligible for meta-analysis. Twenty-four were ineligible because they were the lone study to assess an outcome within an age group,34,36,49,51,52,54 they used the same sample as another study,45 or because data were insufficient to calculate SMDs.19,32,33,42,43,46,47,51 These studies were included in a narrative synthesis.
Characteristics of Included Studies
Studies contained outcomes on 6 648 357 offspring, 375 561 of which were born to a young mother. Sample sizes varied from 42 to 1 826 992 participants.38,50 Offspring ages ranged from 6 months to 40 years.35,37 Across 19 studies, 19 cognitive outcomes were reported. Twenty-seven different studies assessed a total of 56 mental health outcomes, and these were further divided into 2 subcategories. The first (n = 38 outcomes) included externalizing, substance misuse, and antisocial behavior, and the second (n = 18 outcomes) included internalizing and general mental health or illness outcomes. A detailed breakdown of included studies’ characteristics, along with their methods of assessment, can be found in Tables 1 and 2.
Characteristics of Cognitive Outcomes
Author, Year, Country . | Study Design . | N of Offspring of Young Mothers . | N of Offspring of Older Mothers . | Offspring Age . | Outcome(s) Measured . | Measurement(s) Used . | Informant(s) . | Findings for Offspring of Young Mothers . |
---|---|---|---|---|---|---|---|---|
Infant age group | ||||||||
Pomerleau et al, 2003, Canada35 | Prospective Cohort | 23 | 22 | 6 mo | Infant cognitive development | Bayley II MDI | Trained assessor | Lower mental development scores (SMD = 0.78 [95% CI = 0.17 to 1.39]) |
Garcia Coll et al, 1986, United States38 | Prospective cohort | 21 | 21 | 8 mo | Infant cognitive development | Bayley MDI | Trained assessor | Lower mental development scores (SMD = 0.99 [0.35 to 1.64]) |
Hoffman et al, 2015, United States39 | Retrospective cohort | 211 | 1723 | 18–22 mo | Infant cognitive development | Bayley-III MDI | Trained assessor | No significant difference (SMD = 0.07 [−0.07 to 0.21]) |
Rafferty et al, 2011, United States40 | Retrospective cohort | 530 | 710 | 3 y | Infant cognitive development | Bayley MDI | Trained assessor | Lower mental development scores (SMD = 0.21 [0.10 to 0.32]) |
Child age group | ||||||||
Hofferth and Reid, 2002, United States31 | Retrospective cohort | 371 | 2484 | 3+ years | Cognitive functioning | WJRT math score | Trained assessor | Poorer cognitive functioning (SMD = 0.49 [0.38 to 0.60]) |
Gueorguieva et al, 2001, United States41 | Retrospective cohort | 50 416 | 281 050 | 4–6 y | Learning problems | Educational placement in classroom for children with learning problems | Registry-based record linkage | Greater likelihood of placement classroom for children with learning problems (SMD = 0.15 [0.14 to 0.16]) |
Moffitt 2002, United Kingdom59 | Prospective cohort | 1124 | 1108 | 5 y | Cognitive functioning | WPPSI-R IQ score | Trained assessor | Poorer cognitive functioning (SMD = 0.65 [0.57 to 0.74] |
Morinis et al, 2013, United Kingdom33 | Retrospective cohort | 617 | 7004 | 5 y | Cognitive functioning | BAS-II Naming Vocabulary scale | Trained assessor | Poorer cognitive functioning (MD = −8.6 [−10.6 to −6.5]) |
Cornelius et al, 2009, United States42 | Prospective cohort | 355 | 653 | 6 y | Cognitive functioning | Stanford-Binet IQ score | Trained assessor | Lower composite IQ scores (T = −4.61, P <.001) |
Adolescent Age Group | ||||||||
Dahinten et al, 2007, Canada19 | Retrospective cohort | 91 | 1825 | 10–11 y | Cognitive functioning | CAT/2 math score | Objective test | Poorer cognitive functioning (MD = −27.36) |
East and Felice, 1990, United States43 | Case control | 30 | 237 | 12 y | Learning problems | BPC | Teacher | Higher levels of learning problems (SMD = 0.55 [0.17 to 0.93]) |
Shaw et al, 2006, Australia, 17 | Retrospective cohort | 440 | 4536 | 14 y | Learning problems | Grade repetition | Mother | Greater instances of grade failure (SMD = 0.20 [0.06 to 0.34]) |
Coyne et al 2013 (a), Sweden50 | Retrospective cohort | 220 723 | 1 606 269 | 14–15 y | Cognitive functioning | Grade point average | Registry-based record linkage | Poorer cognitive functioning (SMD = 0.51 [0.51 to 0.52]) |
Levine et al, 2007, United States44 | Retrospective cohort | Adolescent and control: 1736 | NR | 14–15 y | Learning problems | NLSY questions about grade repetition | Offspring self-report | Greater likelihood of repeating a grade (SMD = 0.73 [0.45 to 1.02]) |
Levine, et al, 2001, United States45 | Retrospective cohort | Adolescent and control: 1341 | NR | 14–15 y | Learning problems | NLSY questions about grade repetition | Offspring self-report | Greater likelihood of repeating a grade (SMD = 0.63 [95% CI NR]) |
Zimmerman, et al 2001, United States53 | Case control | 64 | 427 | Mean age 14.6 y | Cognitive functioning | Grade point average | Registry-based record linkage | No difference in cognitive functioning (SMD = −0.25 [−0.51 to 0.02]) |
Adult age group | ||||||||
Coyne et al, 2013, Sweden50 | Retrospective cohort | 220 723 | 1 606 269 | 15+ years | Educational attainment | Years of education | Registry-based record linkage | Fewer years of education (SMD = 0.15 [0.15 to 0.16]) |
Khatun et al, 2017, Australia36 | Prospective cohort | 363 | 2280 | 21 y | Cognitive functioning | PPVT-R | Objective test | Lower IQ scores (SMD = −0.32 [−0.43 to −0.21]) |
Lipman et al, 2011, Canada23 | Retrospective cohort | 154 | 2095 | 22–34 y | Educational attainment | Years of education | Offspring self-report | Fewer years of education (SMD = −0.60 [−0.76 to −0.43]) |
Author, Year, Country . | Study Design . | N of Offspring of Young Mothers . | N of Offspring of Older Mothers . | Offspring Age . | Outcome(s) Measured . | Measurement(s) Used . | Informant(s) . | Findings for Offspring of Young Mothers . |
---|---|---|---|---|---|---|---|---|
Infant age group | ||||||||
Pomerleau et al, 2003, Canada35 | Prospective Cohort | 23 | 22 | 6 mo | Infant cognitive development | Bayley II MDI | Trained assessor | Lower mental development scores (SMD = 0.78 [95% CI = 0.17 to 1.39]) |
Garcia Coll et al, 1986, United States38 | Prospective cohort | 21 | 21 | 8 mo | Infant cognitive development | Bayley MDI | Trained assessor | Lower mental development scores (SMD = 0.99 [0.35 to 1.64]) |
Hoffman et al, 2015, United States39 | Retrospective cohort | 211 | 1723 | 18–22 mo | Infant cognitive development | Bayley-III MDI | Trained assessor | No significant difference (SMD = 0.07 [−0.07 to 0.21]) |
Rafferty et al, 2011, United States40 | Retrospective cohort | 530 | 710 | 3 y | Infant cognitive development | Bayley MDI | Trained assessor | Lower mental development scores (SMD = 0.21 [0.10 to 0.32]) |
Child age group | ||||||||
Hofferth and Reid, 2002, United States31 | Retrospective cohort | 371 | 2484 | 3+ years | Cognitive functioning | WJRT math score | Trained assessor | Poorer cognitive functioning (SMD = 0.49 [0.38 to 0.60]) |
Gueorguieva et al, 2001, United States41 | Retrospective cohort | 50 416 | 281 050 | 4–6 y | Learning problems | Educational placement in classroom for children with learning problems | Registry-based record linkage | Greater likelihood of placement classroom for children with learning problems (SMD = 0.15 [0.14 to 0.16]) |
Moffitt 2002, United Kingdom59 | Prospective cohort | 1124 | 1108 | 5 y | Cognitive functioning | WPPSI-R IQ score | Trained assessor | Poorer cognitive functioning (SMD = 0.65 [0.57 to 0.74] |
Morinis et al, 2013, United Kingdom33 | Retrospective cohort | 617 | 7004 | 5 y | Cognitive functioning | BAS-II Naming Vocabulary scale | Trained assessor | Poorer cognitive functioning (MD = −8.6 [−10.6 to −6.5]) |
Cornelius et al, 2009, United States42 | Prospective cohort | 355 | 653 | 6 y | Cognitive functioning | Stanford-Binet IQ score | Trained assessor | Lower composite IQ scores (T = −4.61, P <.001) |
Adolescent Age Group | ||||||||
Dahinten et al, 2007, Canada19 | Retrospective cohort | 91 | 1825 | 10–11 y | Cognitive functioning | CAT/2 math score | Objective test | Poorer cognitive functioning (MD = −27.36) |
East and Felice, 1990, United States43 | Case control | 30 | 237 | 12 y | Learning problems | BPC | Teacher | Higher levels of learning problems (SMD = 0.55 [0.17 to 0.93]) |
Shaw et al, 2006, Australia, 17 | Retrospective cohort | 440 | 4536 | 14 y | Learning problems | Grade repetition | Mother | Greater instances of grade failure (SMD = 0.20 [0.06 to 0.34]) |
Coyne et al 2013 (a), Sweden50 | Retrospective cohort | 220 723 | 1 606 269 | 14–15 y | Cognitive functioning | Grade point average | Registry-based record linkage | Poorer cognitive functioning (SMD = 0.51 [0.51 to 0.52]) |
Levine et al, 2007, United States44 | Retrospective cohort | Adolescent and control: 1736 | NR | 14–15 y | Learning problems | NLSY questions about grade repetition | Offspring self-report | Greater likelihood of repeating a grade (SMD = 0.73 [0.45 to 1.02]) |
Levine, et al, 2001, United States45 | Retrospective cohort | Adolescent and control: 1341 | NR | 14–15 y | Learning problems | NLSY questions about grade repetition | Offspring self-report | Greater likelihood of repeating a grade (SMD = 0.63 [95% CI NR]) |
Zimmerman, et al 2001, United States53 | Case control | 64 | 427 | Mean age 14.6 y | Cognitive functioning | Grade point average | Registry-based record linkage | No difference in cognitive functioning (SMD = −0.25 [−0.51 to 0.02]) |
Adult age group | ||||||||
Coyne et al, 2013, Sweden50 | Retrospective cohort | 220 723 | 1 606 269 | 15+ years | Educational attainment | Years of education | Registry-based record linkage | Fewer years of education (SMD = 0.15 [0.15 to 0.16]) |
Khatun et al, 2017, Australia36 | Prospective cohort | 363 | 2280 | 21 y | Cognitive functioning | PPVT-R | Objective test | Lower IQ scores (SMD = −0.32 [−0.43 to −0.21]) |
Lipman et al, 2011, Canada23 | Retrospective cohort | 154 | 2095 | 22–34 y | Educational attainment | Years of education | Offspring self-report | Fewer years of education (SMD = −0.60 [−0.76 to −0.43]) |
BAS-II, British Ability Scale second Edition; BPC, Behavior Problem Checklist; CAT/2, Canadian Achievement Test, second edition; CPRS-48, 48-Item Conners Parental Rating Scale; MDI, Mental Development Indices; NLSY, National Longitudinal Survey of Youth; NR, not reported; PPVT-R, Peabody Picture Vocabulary Test-Revised; WJRT, Woodcock-Johnson Revised Test of Achievement; WPPSI-R, Wechsler Preschool and Primary Scale of Intelligence-Revised.
Characteristics of Mental Health Outcomes
Author, Year, Country . | Study Design . | N of Offspring of Young Mothers . | N of Offspring of Older Mothers . | Offspring Age . | Outcome(s) Measured . | Measurement(s) Used . | Informant(s) . | Findings for Offspring of Young Mothers . |
---|---|---|---|---|---|---|---|---|
Externalizing, substance misuse, and criminal behavior | ||||||||
Infant age group | ||||||||
Agnafors et al, 2019, Sweden53 | Prospective cohort | 61 | 1 662 | 3 y | Externalizing | CBCL | Mother | Higher levels of externalizing (SMD = 0.45[0.01 to 0.89]) |
Child age group | ||||||||
Chang et al, 2014, Sweden46 | Retrospective cohort | Adolescent and control: 1 495 543 | NR | Children (specific ages NR) | ADHD | National patient registry of ADHD diagnosis or treatment with ADHD medication | Registry-based record linkage | Greater risk of ADHD (HR = 1.78 [1.72 to 1.84]) |
Guèvremont and Kohen, 2012, Canada57 | Cross-sectional | 306 | 147 | 2–5 y | Conduct problems, hyperactivity | Goodman SDQ, Goodman SDQ | Parent, parent | No significant difference in levels of conduct problems (SMD = 0.18 [−0.01 to 0.38]); no significant difference in levels of hyperactivity (SMD = 0.09 [−0.10 to 0.29]) |
Guèvremont and Kohen, 2013, Canada58 | Cross-sectional | 807 | 916 | 2–5 y | Conduct problems, hyperactivity | Goodman SDQ, Goodman SDQ | Parent, parent | Significant association with conduct problems (β = 0.16, SE = 0.02, P <.001); significant association with hyperactivity (β = 0.16, SE = 0.03, P <.001) |
Moffitt 2002, United Kingdom59 | Prospective cohort | 1124 | 1108 | 5 y | Externalizing, hyperactivity | CBCL, 17 items from RCS supplemented with items from DSM-IV | Mother, mother | Higher levels of externalizing (SMD = 0.51 [0.42 to 0.59]; higher levels of hyperactivity (SMD = 0.33 [0.24 to 0.41]) |
Christ et al, 1990, United States47 | Retrospective cohort | Adolescent and control: 253 | NR | 6–13 y | Conduct disorder | DSM-III | Offspring self-report | Significant association with conduct disorder (β = 0.253, P <.01) |
Adolescent age group | ||||||||
Chudal et al, 2015, Finland55 | Case control | 1647 | 47 886 | 4–20 y | ADHD | National patient registry of ADHD diagnosis | Registry-based record linkage | Higher likelihood of ADHD diagnosis (SMD = 0.61 [0.55 to 0.66]) |
Dahinten et al, 2007, Canada19 | Retrospective cohort | 91 | 1825 | 10–11 y | Delinquency, hyperactivity | CBCL, CBCL | Offspring self-report, offspring self-report | No significant difference in delinquency (MD = 0.01); no significant difference in hyperactivity (MD = 0.00) |
Lee et al, 2017, Taiwan18 | Prospective cohort | 107 | 111 | 10–12 y | Behavioral problems, hyperactivity | CTRS-28, CTRS-28 | Teacher, teacher | Higher levels of behavioral problems (SMD = 0.34 [0.08 to 0.60]); higher levels of hyperactivity (SMD = 0.38 [0.12 to 0.64]) |
Menard et al, 2015, United States48 | Retrospective cohort | 1713 | 1231 | 11–14 y | Delinquency, substance misuse, hyperactivity | BPI, BPI, BPI | Mother, mother, mother | Higher levels of delinquency (SMD = 0.20 [0.12 to 0.28]); higher levels of substance misuse (SMD = 0.37 [0.27 to 0.47]); higher levels of hyperactivity (SMD = 0.42 [0.33 to 0.51]) |
East and Felice, 1990, United States43 | Case control | 30 | 237 | 12 y | Behavioral problems | BPC | Teacher, mother | No difference in behavioral problems (F<1) |
Barnes and Morris, 2012, United States20 | Retrospective cohort | 1464 | 11 543 | 12–18 y | Delinquency | 17-item questionnaire of involvement in delinquent activities | Offspring self-report | Greater participation in delinquent activities (SMD = 0.10 [0.05 to 0.15]) |
Shaw et al, 2006, Australia17 | Retrospective cohort | 440 | 4536 | 14 y | Delinquency, substance misuse | YSR, interview about smoking in previous week | Offspring self-report, offspring self-report | Higher levels of delinquency (SMD = 0.36 [0.20 to 0.51]); greater instances of substance misuse (SMD = 0.41 [0.21 to 0.61]) |
Levine et al, 2007, United States44 | Retrospective cohort | Adolescent and control: 1736 | NR | 14–15 y | Delinquency, substance misuse | NLSY questions about fighting at work or school, NLSY questions about cannabis use | Offspring self-report, offspring self-report | Greater likelihood of fighting (SMD = 0.61 [0.35 to 0.87]); no greater likelihood of cannabis usage SMD = 0.15 [−0.16 to 0.41]) |
Levine et al, 2001, United States45 | Retrospective cohort | Adolescent and control: 1341 | NR | 14–15 y | Delinquency, substance misuse | NLSY questions about fighting at work or school, NLSY questions about cannabis use | Offspring self-report, offspring self-report | Greater likelihood of fighting (SMD = 0.59 [95% CI NR]); greater likelihood of using cannabis (SMD = 0.13 [95% CI NR]) |
Zimmerman et al, 2001 (sample 1), United States53 | Case control | 64 | 427 | Mean age 14.6 y | Delinquency, substance misuse | Interview about frequency of delinquent acts, interview about frequency of cannabis use | Offspring self-report, offspring self-report | No difference in delinquency (SMD = 0.02 [−0.24 to 0.28]); no difference in substance misuse (SMD = 0.16 [−0.11 to 0.42]) |
Pogarsky et al 2003, United States32 | Retrospective cohort | Adolescent and control: 781 | NR | 15.5–17.5 y | Delinquency | Interview about the number of times the subject committed each of 31 acts of delinquency | Offspring self-report | Greater instances of delinquency (incidence of 47% vs. 21%) |
Zimmerman et al, 2001 (sample 1), United States53 | Case control | 39 | 128 | Mean age 16.9 y | Delinquency, substance misuse | Interview about frequency of delinquent acts, interview about frequency of cannabis use | Offspring self-report, offspring self-report | No difference in delinquency (SMD = 0.11 [−0.25 to 0.46]); no difference in substance misuse (SMD = −0.25 [−0.61 to 0.11]) |
Silva et al, 2014, Australia56 | Case control | 523 | 9318 | <25 y | ADHD | National patient registry of prescription of ADHD medication | Registry-based record linkage | Higher likelihood of ADHD (SMD = 0.25 [0.14 to 0.36]) |
Adult age group | ||||||||
Harden et al, 2007, Australia49 | Retrospective cohort | 91 | 1277 | 14–39 y | Substance misuse, conduct disorder | SSAGA-OZ phone interview, SSAGA-OZ phone interview | Offspring self-report, offspring self-report | Greater instances of substance misuse (SMD = 0.37 [0.15 to 0.59]); higher levels of conduct disorder (SMD = 0.42 [0.21 to 0.64]) |
Mok et al, 2017, Denmark37 | Prospective cohort | 92 713 | 1 700 968 | 15–40 y | Violent criminal convictions, substance misuse | Number of violent criminal convictions, number of drug-related criminal convictions | Registry-based record linkage, registry-based record linkage | Greater likelihood of committing a violent crime (SMD = 0.29 [0.27 to 0.30]); greater likelihood of misusing substances (SMD = 0.59 [0.56 to 0.61]) |
Coyne et al, 2013 (a), Sweden50 | Retrospective cohort | 220 723 | 1 606 269 | 15+ years | Violent criminal convictions, substance misuse | Number of violent criminal convictions, number of drug-related criminal convictions | Registry-based record linkage, registry-based record linkage | Greater instances of violent criminal convictions (SMD = 0.43 [0.43 to 0.44]); greater instances of substance-related hospitalizations (SMD = 0.34 [0.32 to 0.35]) |
Coyne et al, 2013 (b), Sweden51 | Retrospective cohort | Adolescent and control: 1 084 939 | NR | 15+ years | Criminal convictions | Number of criminal convictions | Registry-based record linkage | Increased rates of criminal conviction (HR = 1.64, P <.0001) |
Internalizing and general mental health | ||||||||
Infant age group | ||||||||
Andreozzi et al, 2002, United States34 | Prospective cohort | 51 | 76 | 18 mo | Maternal attachment | Ainsworth’s Strange Situation Task | Trained assessor | No difference of secure versus insecure attachment (χ2= 0.003, P = .99) |
Agnafors et al, 2019, Sweden54 | Prospective cohort | 61 | 1 662 | 3 y | Internalizing | CBCL | Mother | Higher levels of internalizing (SMD = 0.48 [0.04 to 0.92]) |
Child age group | ||||||||
Guèvremont and Kohen, 2012, Canada57 | Cross-sectional | 306 | 147 | 2–5 y | Emotional symptoms | Goodman SDQ | Parent | Higher levels of emotional symptoms (SMD = 0.37 [0.18 to 0.57]) |
Guèvremont and Kohen, 2013, Canada58 | Cross-sectional | 1153 | 1252 | 2–5 y | Emotional symptoms | Goodman SDQ | Parent | Significant association with emotional symptoms (β= 0.04, SE = 0.02, P <.05) |
Hofferth and Reid, 2002, United States31 | Retrospective cohort | 371 | 2484 | 3+ years | Internalizing | BPI | Offspring self-report | Higher levels of internalizing (SMD = 0.16 [0.05 to 0.27]) |
Moffitt 2002, United Kingdom59 | Prospective cohort | 1124 | 1108 | 5 y | Internalizing | CBCL | Mother | Higher levels of internalizing (SMD = 0.37 [0.29 to 0.46]) |
Adolescent age group | ||||||||
Dahinten et al, 2007, Canada19 | Retrospective cohort | 91 | 1825 | 10–11 y | Anxiety | CBCL | Offspring self-report | No significant difference in anxiety (MD = −0.06) |
Lee et al, 2017, Taiwan18 | Prospective cohort | 107 | 111 | 10–12 y | Anxiety | CPRS-48 | Parent | Lower levels of anxiety (SMD = −0.28 [−0.54 to −0.02]) |
East and Felice, 1990, United States43 | Case control | 30 | 237 | 12 y | Psychological functioning | SPP, UCLALS, CES-DC | Offspring self-report | No difference in psychological functioning (F<1) |
Zilikis et al, 2012, Greece52 | Case control | 160 | 160 | 12–19 y | Suicidal ideation | Admission to psychiatric unit | Registry-based record linkage | Greater admissions for suicidal ideation (SMD = 0.71, P = .001) |
Shaw et al, 2006, Australia17 | Retrospective cohort | 440 | 4536 | 14 y | Depression | YSR | Offspring self-report | Higher levels of depression (SMD = 0.20 [0.04 to 0.37]) |
Zimmerman 2001 (Sample 1), United States53 | Case control | 39 | 128 | Mean age 16.9 y | Anxiety, depression | BSI anxiety subscale, BSI depression subscale | Offspring self-report, offspring self-report | No difference in anxiety (SMD = −0.09 [−0.44 to 0.26]); no difference in depression (SMD = −0.04 [−0.40 to 0.32]) |
Zimmerman, et al, 2001 (Sample 2), United States53 | Case control | 64 | 427 | Mean age 14.6 y | Anxiety, depression | BSI anxiety subscale, BSI depression subscale | Offspring self-report, offspring self-report | No difference in anxiety (SMD = 0.05 [−0.21 to 0.31]); no difference in depression (SMD = 0.03 [−0.23 to 0.29]) |
Adult age group | ||||||||
Harden et al, 2007, Australia49 | Retrospective cohort | 91 | 1277 | 14–39 y | General mental health | SSAGA-OZ phone interview | Offspring self-report | Higher levels of mental illness (SMD = 0.23 [0.02 to 0.44]) |
Mok et al, 2017, Denmark37 | Prospective cohort | 92 713 | 1 700 968 | 15–40 y | General mental health | National hospital registry of suicide attempts and history of mental illness | Registry-based record linkage | Greater likelihood of mental illness diagnosis (SMD = 0.35 [0.34 to 0.36]) |
Lipman et al, 2011, Canada23 | Retrospective cohort | 154 | 2095 | 22–34 y | General mental health | SF-12 | Offspring self-report | Higher levels of mental illness (SMD = 0.28 [0.12 to 0.44]) |
Author, Year, Country . | Study Design . | N of Offspring of Young Mothers . | N of Offspring of Older Mothers . | Offspring Age . | Outcome(s) Measured . | Measurement(s) Used . | Informant(s) . | Findings for Offspring of Young Mothers . |
---|---|---|---|---|---|---|---|---|
Externalizing, substance misuse, and criminal behavior | ||||||||
Infant age group | ||||||||
Agnafors et al, 2019, Sweden53 | Prospective cohort | 61 | 1 662 | 3 y | Externalizing | CBCL | Mother | Higher levels of externalizing (SMD = 0.45[0.01 to 0.89]) |
Child age group | ||||||||
Chang et al, 2014, Sweden46 | Retrospective cohort | Adolescent and control: 1 495 543 | NR | Children (specific ages NR) | ADHD | National patient registry of ADHD diagnosis or treatment with ADHD medication | Registry-based record linkage | Greater risk of ADHD (HR = 1.78 [1.72 to 1.84]) |
Guèvremont and Kohen, 2012, Canada57 | Cross-sectional | 306 | 147 | 2–5 y | Conduct problems, hyperactivity | Goodman SDQ, Goodman SDQ | Parent, parent | No significant difference in levels of conduct problems (SMD = 0.18 [−0.01 to 0.38]); no significant difference in levels of hyperactivity (SMD = 0.09 [−0.10 to 0.29]) |
Guèvremont and Kohen, 2013, Canada58 | Cross-sectional | 807 | 916 | 2–5 y | Conduct problems, hyperactivity | Goodman SDQ, Goodman SDQ | Parent, parent | Significant association with conduct problems (β = 0.16, SE = 0.02, P <.001); significant association with hyperactivity (β = 0.16, SE = 0.03, P <.001) |
Moffitt 2002, United Kingdom59 | Prospective cohort | 1124 | 1108 | 5 y | Externalizing, hyperactivity | CBCL, 17 items from RCS supplemented with items from DSM-IV | Mother, mother | Higher levels of externalizing (SMD = 0.51 [0.42 to 0.59]; higher levels of hyperactivity (SMD = 0.33 [0.24 to 0.41]) |
Christ et al, 1990, United States47 | Retrospective cohort | Adolescent and control: 253 | NR | 6–13 y | Conduct disorder | DSM-III | Offspring self-report | Significant association with conduct disorder (β = 0.253, P <.01) |
Adolescent age group | ||||||||
Chudal et al, 2015, Finland55 | Case control | 1647 | 47 886 | 4–20 y | ADHD | National patient registry of ADHD diagnosis | Registry-based record linkage | Higher likelihood of ADHD diagnosis (SMD = 0.61 [0.55 to 0.66]) |
Dahinten et al, 2007, Canada19 | Retrospective cohort | 91 | 1825 | 10–11 y | Delinquency, hyperactivity | CBCL, CBCL | Offspring self-report, offspring self-report | No significant difference in delinquency (MD = 0.01); no significant difference in hyperactivity (MD = 0.00) |
Lee et al, 2017, Taiwan18 | Prospective cohort | 107 | 111 | 10–12 y | Behavioral problems, hyperactivity | CTRS-28, CTRS-28 | Teacher, teacher | Higher levels of behavioral problems (SMD = 0.34 [0.08 to 0.60]); higher levels of hyperactivity (SMD = 0.38 [0.12 to 0.64]) |
Menard et al, 2015, United States48 | Retrospective cohort | 1713 | 1231 | 11–14 y | Delinquency, substance misuse, hyperactivity | BPI, BPI, BPI | Mother, mother, mother | Higher levels of delinquency (SMD = 0.20 [0.12 to 0.28]); higher levels of substance misuse (SMD = 0.37 [0.27 to 0.47]); higher levels of hyperactivity (SMD = 0.42 [0.33 to 0.51]) |
East and Felice, 1990, United States43 | Case control | 30 | 237 | 12 y | Behavioral problems | BPC | Teacher, mother | No difference in behavioral problems (F<1) |
Barnes and Morris, 2012, United States20 | Retrospective cohort | 1464 | 11 543 | 12–18 y | Delinquency | 17-item questionnaire of involvement in delinquent activities | Offspring self-report | Greater participation in delinquent activities (SMD = 0.10 [0.05 to 0.15]) |
Shaw et al, 2006, Australia17 | Retrospective cohort | 440 | 4536 | 14 y | Delinquency, substance misuse | YSR, interview about smoking in previous week | Offspring self-report, offspring self-report | Higher levels of delinquency (SMD = 0.36 [0.20 to 0.51]); greater instances of substance misuse (SMD = 0.41 [0.21 to 0.61]) |
Levine et al, 2007, United States44 | Retrospective cohort | Adolescent and control: 1736 | NR | 14–15 y | Delinquency, substance misuse | NLSY questions about fighting at work or school, NLSY questions about cannabis use | Offspring self-report, offspring self-report | Greater likelihood of fighting (SMD = 0.61 [0.35 to 0.87]); no greater likelihood of cannabis usage SMD = 0.15 [−0.16 to 0.41]) |
Levine et al, 2001, United States45 | Retrospective cohort | Adolescent and control: 1341 | NR | 14–15 y | Delinquency, substance misuse | NLSY questions about fighting at work or school, NLSY questions about cannabis use | Offspring self-report, offspring self-report | Greater likelihood of fighting (SMD = 0.59 [95% CI NR]); greater likelihood of using cannabis (SMD = 0.13 [95% CI NR]) |
Zimmerman et al, 2001 (sample 1), United States53 | Case control | 64 | 427 | Mean age 14.6 y | Delinquency, substance misuse | Interview about frequency of delinquent acts, interview about frequency of cannabis use | Offspring self-report, offspring self-report | No difference in delinquency (SMD = 0.02 [−0.24 to 0.28]); no difference in substance misuse (SMD = 0.16 [−0.11 to 0.42]) |
Pogarsky et al 2003, United States32 | Retrospective cohort | Adolescent and control: 781 | NR | 15.5–17.5 y | Delinquency | Interview about the number of times the subject committed each of 31 acts of delinquency | Offspring self-report | Greater instances of delinquency (incidence of 47% vs. 21%) |
Zimmerman et al, 2001 (sample 1), United States53 | Case control | 39 | 128 | Mean age 16.9 y | Delinquency, substance misuse | Interview about frequency of delinquent acts, interview about frequency of cannabis use | Offspring self-report, offspring self-report | No difference in delinquency (SMD = 0.11 [−0.25 to 0.46]); no difference in substance misuse (SMD = −0.25 [−0.61 to 0.11]) |
Silva et al, 2014, Australia56 | Case control | 523 | 9318 | <25 y | ADHD | National patient registry of prescription of ADHD medication | Registry-based record linkage | Higher likelihood of ADHD (SMD = 0.25 [0.14 to 0.36]) |
Adult age group | ||||||||
Harden et al, 2007, Australia49 | Retrospective cohort | 91 | 1277 | 14–39 y | Substance misuse, conduct disorder | SSAGA-OZ phone interview, SSAGA-OZ phone interview | Offspring self-report, offspring self-report | Greater instances of substance misuse (SMD = 0.37 [0.15 to 0.59]); higher levels of conduct disorder (SMD = 0.42 [0.21 to 0.64]) |
Mok et al, 2017, Denmark37 | Prospective cohort | 92 713 | 1 700 968 | 15–40 y | Violent criminal convictions, substance misuse | Number of violent criminal convictions, number of drug-related criminal convictions | Registry-based record linkage, registry-based record linkage | Greater likelihood of committing a violent crime (SMD = 0.29 [0.27 to 0.30]); greater likelihood of misusing substances (SMD = 0.59 [0.56 to 0.61]) |
Coyne et al, 2013 (a), Sweden50 | Retrospective cohort | 220 723 | 1 606 269 | 15+ years | Violent criminal convictions, substance misuse | Number of violent criminal convictions, number of drug-related criminal convictions | Registry-based record linkage, registry-based record linkage | Greater instances of violent criminal convictions (SMD = 0.43 [0.43 to 0.44]); greater instances of substance-related hospitalizations (SMD = 0.34 [0.32 to 0.35]) |
Coyne et al, 2013 (b), Sweden51 | Retrospective cohort | Adolescent and control: 1 084 939 | NR | 15+ years | Criminal convictions | Number of criminal convictions | Registry-based record linkage | Increased rates of criminal conviction (HR = 1.64, P <.0001) |
Internalizing and general mental health | ||||||||
Infant age group | ||||||||
Andreozzi et al, 2002, United States34 | Prospective cohort | 51 | 76 | 18 mo | Maternal attachment | Ainsworth’s Strange Situation Task | Trained assessor | No difference of secure versus insecure attachment (χ2= 0.003, P = .99) |
Agnafors et al, 2019, Sweden54 | Prospective cohort | 61 | 1 662 | 3 y | Internalizing | CBCL | Mother | Higher levels of internalizing (SMD = 0.48 [0.04 to 0.92]) |
Child age group | ||||||||
Guèvremont and Kohen, 2012, Canada57 | Cross-sectional | 306 | 147 | 2–5 y | Emotional symptoms | Goodman SDQ | Parent | Higher levels of emotional symptoms (SMD = 0.37 [0.18 to 0.57]) |
Guèvremont and Kohen, 2013, Canada58 | Cross-sectional | 1153 | 1252 | 2–5 y | Emotional symptoms | Goodman SDQ | Parent | Significant association with emotional symptoms (β= 0.04, SE = 0.02, P <.05) |
Hofferth and Reid, 2002, United States31 | Retrospective cohort | 371 | 2484 | 3+ years | Internalizing | BPI | Offspring self-report | Higher levels of internalizing (SMD = 0.16 [0.05 to 0.27]) |
Moffitt 2002, United Kingdom59 | Prospective cohort | 1124 | 1108 | 5 y | Internalizing | CBCL | Mother | Higher levels of internalizing (SMD = 0.37 [0.29 to 0.46]) |
Adolescent age group | ||||||||
Dahinten et al, 2007, Canada19 | Retrospective cohort | 91 | 1825 | 10–11 y | Anxiety | CBCL | Offspring self-report | No significant difference in anxiety (MD = −0.06) |
Lee et al, 2017, Taiwan18 | Prospective cohort | 107 | 111 | 10–12 y | Anxiety | CPRS-48 | Parent | Lower levels of anxiety (SMD = −0.28 [−0.54 to −0.02]) |
East and Felice, 1990, United States43 | Case control | 30 | 237 | 12 y | Psychological functioning | SPP, UCLALS, CES-DC | Offspring self-report | No difference in psychological functioning (F<1) |
Zilikis et al, 2012, Greece52 | Case control | 160 | 160 | 12–19 y | Suicidal ideation | Admission to psychiatric unit | Registry-based record linkage | Greater admissions for suicidal ideation (SMD = 0.71, P = .001) |
Shaw et al, 2006, Australia17 | Retrospective cohort | 440 | 4536 | 14 y | Depression | YSR | Offspring self-report | Higher levels of depression (SMD = 0.20 [0.04 to 0.37]) |
Zimmerman 2001 (Sample 1), United States53 | Case control | 39 | 128 | Mean age 16.9 y | Anxiety, depression | BSI anxiety subscale, BSI depression subscale | Offspring self-report, offspring self-report | No difference in anxiety (SMD = −0.09 [−0.44 to 0.26]); no difference in depression (SMD = −0.04 [−0.40 to 0.32]) |
Zimmerman, et al, 2001 (Sample 2), United States53 | Case control | 64 | 427 | Mean age 14.6 y | Anxiety, depression | BSI anxiety subscale, BSI depression subscale | Offspring self-report, offspring self-report | No difference in anxiety (SMD = 0.05 [−0.21 to 0.31]); no difference in depression (SMD = 0.03 [−0.23 to 0.29]) |
Adult age group | ||||||||
Harden et al, 2007, Australia49 | Retrospective cohort | 91 | 1277 | 14–39 y | General mental health | SSAGA-OZ phone interview | Offspring self-report | Higher levels of mental illness (SMD = 0.23 [0.02 to 0.44]) |
Mok et al, 2017, Denmark37 | Prospective cohort | 92 713 | 1 700 968 | 15–40 y | General mental health | National hospital registry of suicide attempts and history of mental illness | Registry-based record linkage | Greater likelihood of mental illness diagnosis (SMD = 0.35 [0.34 to 0.36]) |
Lipman et al, 2011, Canada23 | Retrospective cohort | 154 | 2095 | 22–34 y | General mental health | SF-12 | Offspring self-report | Higher levels of mental illness (SMD = 0.28 [0.12 to 0.44]) |
BPC, Behavior Problem Checklist; BPI, Behavior Problems Index; BSI, Brief Symptom Inventory; CBCL, Child Behavior Checklist; CES-DC, Center for Epidemiologic Studies Depression Scale for Children; CPRS-48 = 48-Item Conners Parent Rating Scale; CTRS-28, 28-Item Conners Teachers Rating Scale; DSM-III, Diagnostic and Statistical Manual of Mental Disorders third Edition; DSM-IV, Diagnostic and Statistical Manual of Mental Disorders fourth Edition; NLSY, National Longitudinal Survey of Youth; NR, not reported; RCS, Rutter Child Scales; SDQ, Strengths and Difficulties Questionnaire; SF-12, 12-Item Short Form Health Survey; SPP, Self Perception Profile; SSAGA-OZ, Semi-Structured Assessment for the Genetics of Alcoholism-Australian Version; UCLALS, University of California, Los Angeles Loneliness Scale; YSR, Achenbach’s Youth Self Report.
Twenty-one studies were rated at low risk of bias (defined as >7 stars on a Newcastle-Ottawa scale) and eleven moderate risk (6–7 stars). Three were deemed at high risk of bias (0–5 stars) because case and control groups were not representative of the broader population (eg, recruited only from a psychiatric unit) (Supplemental Tables 3A–3C). Other common bias sources included small or inadequate sample sizes and self-reported outcomes. Visual inspection of funnel plots revealed no asymmetry, suggesting a low risk of publication bias for all meta-analyses.
Cognitive Functioning
Of the 19 cognitive outcomes, 17 reported that young mothers’ offspring experience greater cognitive or learning problems and/or achieve fewer years of education. Fourteen cognitive outcomes were pooled in 4 meta-analyses: infant cognitive problems (n = 4 outcomes), child cognitive and learning problems (n = 3), adolescent cognitive, and learning problems (n = 5) (Fig 2), and adult educational attainment (n = 2). The offspring of young mothers had poorer cognitive function as infants (SMD = 0.30 [0.06 to 0.55] I2 = 76%),35,38–40 children (SMD = 0.43 [0.07 to 0.79] I2 = 99%),31,41,59 and as adolescents (SMD = 0.43 [0.24 to 0.62] I2 = 82%).17,43,44,53 Our meta-analyses showed no difference in adult educational attainment (SMD = −0.37 [−0.81 to 0.07] I2 = 97%) (Supplemental Fig 4A).23,50 No subgroup analyses were conducted because of a lack of uniform reporting of separate data, and sensitivity analyses did not reveal any significant differences in our findings (Supplemental Table 4).
The 5 cognitive outcomes that could not be meta-analyzed suggested that the offspring of young mothers have poorer cognitive functioning. Morinis et al and Cornelius and colleagues suggested that the cognitive functioning of children born to young mothers was worse than their counterparts at 5 (MD = −8.6 [−10.6 to −6.5]) and 6 years using the BAS-II Naming Vocabulary scale and the Stanford-Binet IQ score, respectively.33,42 Dahinten and colleagues also showed 10 to 11-year-olds had poorer math scores on the CAT/2.19 This was consistent with Levine et al’s finding that young mothers’ offspring were more likely to repeat a grade by 14–15 years (SMD = 0.63),45 and Khatun et al’s report that 21-year-olds born to young mothers had lower IQs (SMD = −0.32 [−0.43 to −0.21]).37
Mental Health
Externalizing, Substance Misuse, and Criminal Behavior
Thirty-eight externalizing, substance misuse, and criminal behavior outcomes were assessed and 28 reported increased risk in the offspring of young mothers. Seven meta-analyses were generated: child externalizing (n = 2 outcomes), child hyperactivity (n = 2), adolescent delinquency or conduct disorder (n = 7) (Fig 3), adolescent substance misuse (n = 5), adolescent hyperactivity and ADHD (n = 4), adult violent criminal convictions (n = 2), and adult substance misuse (n = 3).
As children, the offspring of young mothers exhibit somewhat higher levels of externalizing than their peers (SMD = 0.36 [0.03 to 0.68] I2 = 89%)57,59 and are more hyperactive (SMD = 0.28 [0.14 to 0.42] I2 = 48%).57,59 These trends persist into adolescence, where they have more symptoms of delinquency and conduct disorder (SMD = 0.24 [0.12 to 0.36] I2 = 77%),17,18,20,44,48,53 substance misuse (SMD = 0.21 [0.03 to 0.40] I2 = 72%),17,44,48,53 and hyperactivity (SMD = 0.42 [0.34 to 0.50] I2 = 0%).18,48,55,56 As adults, they are more likely to be convicted of violent crimes (SMD = 0.36 [0.22 to 0.50] I2 = 100%),37,50 and to misuse substances (SMD = 0.44 [0.23 to 0.65] I2 = 99%) (Supplemental Fig 4B).37,49,50 No subgroup analyses were conducted because of a lack of uniform reporting of separate data on offspring sex, birth order, and paternal presence from each study, and sensitivity analyses did not reveal any significant differences in our findings (Supplemental Table 4).
Of the 13 outcomes that could not be meta-analyzed, Agnafors et al showed young mothers reported more externalizing symptoms in their 3-year-olds on the Child Behavior Checklist (CBCL) (SMD = 0.45 [0.01 to 0.89]),54 and Christ et al found these offspring were more likely to self-report DSM-III symptoms of conduct disorder at ages 6 to 13.47 Guèvremont and colleagues found young parents reported more conduct problems and hyperactivity in their children on the Strengths and Difficulties Questionnaire (SDQ).58 Chang et al reported these children had 78% higher odds of ADHD diagnosis or being treated for it (hazard ratio [HR] = 1.78 [1.72 to 1.84]).46 Dahinten et al also reported no difference between young mothers’ offspring and controls in self-reported delinquency or hyperactivity at 10 to 11 years on the CBCL.19 East et al also found no difference in behavioral problems in 12-year-olds as reported by their teachers and mothers on the BPC.43 However, Levine et al showed the 14 to 15-year-old offspring of young mothers were more likely to report fighting at work or school (SMD = 0.59) and using cannabis (SMD = 0.13).45 Pogarsky et al further reported that, in a group of adolescents, 47% of those born to young mothers admitted to engaging in delinquent acts, compared with 21% of controls.32 Harden et al further found 14 to 39-year-old offspring self-reported more symptoms of conduct disorder.49 Finally, Coyne et al used crime registry linkage to show these offspring were more likely to be convicted of a crime as adults (HR = 1.64).51
Internalizing and General Mental Health
Of the 18 internalizing and general mental health outcomes in the included studies, 11 reported that the offspring of young mothers experienced more problems. Seven showed no difference, and a lone study found levels of anxiety were lower in young mothers’ offspring. Three meta-analyses were conducted: child internalizing (n = 3 outcomes), adolescent anxiety (n = 3), adolescent depression (n = 3), and adult general mental illness (n = 3).
The offspring of young mothers have higher levels of overall internalizing symptoms as children (SMD = 0.29 [0.14 to 0.45] I2 = 79%),31,57,59 but not anxiety (SMD = −0.11 [−0.31 to 0.10] I2 = 34%),18,53 or depression (SMD = 0.12 [−0.01 to 0.26] I2 = 5%) as adolescents.17,53 As adults, they are more likely to experience mental illness (SMD = 0.35 [0.34 to 0.36] I2 = 0%) (Fig 4) (Supplemental Fig 4C).23,37,49 No subgroup analyses were conducted because of a lack of uniform reporting of separate data, and sensitivity analyses did not reveal any significant differences in our findings (Supplemental Table 4).
Six internalizing and general mental health outcomes could not be meta-analyzed. Andreozzi et al examined maternal-infant attachment of 18-month-olds using Ainsworth’s strange situation task and found no difference between these groups in secure versus insecure attachment (χ2 = 0.003, P = .99).34 Agnafors and colleagues showed young mothers reported higher levels of internalizing in their 3-year-olds on the CBCL (SMD = 0.48 [0.04 to 0.92]),54 and Guèvremont et al found young parents reported more emotional symptoms in their 2 to 5-year-olds on the SDQ.58
Among adolescents, Dahinten et al showed the offspring of young mothers self-reported being no more anxious than their peers,19 and East and colleagues found no difference in overall self-reported general psychological functioning.43 One case-control study by Zilikis suggested the adolescents of young mothers were more often admitted to psychiatric units for suicidal ideation (SMD = 0.71).52
Discussion
Across 35 studies, we extracted data on 19 cognitive and 56 mental health outcomes in over 6 million offspring from 6 months to 40 years of age. Our meta-analyses suggest that the offspring of young mothers have delayed cognitive development in infancy, struggle more with school during childhood and adolescence, and may attain fewer years of education by adulthood. More symptoms of hyperactivity are seen in these children, and externalizing, substance misuse, and criminal behavior are more common during their adolescence and adulthood. Findings for internalizing psychopathology are mixed, with higher levels in childhood but not adolescence and elevated rates in adulthood. The effect sizes of these findings are small but largely consistent with those in our narrative synthesis and suggest being born to a young mother has adverse effects on cognitive function and mental health across the lifespan.
Disparities in cognitive functioning are present as early as 6 months and may not resolve as offspring age. The magnitude of this effect may be even larger than the impact of socioeconomic disadvantage,60 though we caution comparing these outcomes without acknowledging the likely confounding relationship between them. Nonetheless, our findings illustrate the negative cognitive impact of being born to a young mother and suggest that this exposure alone is useful for identifying offspring who may be at risk. Still, the mechanisms by which this risk develops and persists are unclear. Socioeconomic challenges may contribute along with higher rates of pregnancy and delivery complications.61 Later postnatal environmental factors likely also play a role. Young mothers experience more stressors and receive less support, which may compromise their focus on their offspring62 and impair their ability to provide as much stimulation as mothers ≥21.63
Findings of increased levels of externalizing, substance misuse, and criminal behavior were similarly persistent. These offspring are more prone to symptoms of externalizing and hyperactivity as children, and increased levels of ADHD, substance misuse, and delinquency are seen in adolescence. This is consistent with Lee et al’s meta-analysis,21 and suggests being born to a young mother is also a useful exposure for estimating risk of externalizing and criminal behaviors. Confounding factors notwithstanding, it may be an even stronger predictor of externalizing than being a victim of abuse or experiencing socioeconomic disadvantages.64
Although the mechanisms underlying these findings are not entirely understood, young mothers may have higher levels of externalizing problems themselves, suggesting that genetics and the early environment play a key role. Young mothers may also apply discipline less consistently and/or use more coercive parenting,65 which can negatively influence their ability to regulate emotions.67 Externalizing problems generally exhibit homotypic continuity, and the home environments provided by young mothers may continue to contribute to a higher risk of delinquency in offspring as they mature.67
Young mothers’ offspring also appear more prone to internalizing problems. Being born to a young mother was associated with higher levels of internalizing symptoms in children and increased the likelihood of mental illness diagnoses in adulthood. These increased risks could be contributed to by genetic inheritance along with parental stress and relationship challenges.68,69 It should also be noted that two-thirds of the samples in the adolescent anxiety and depression meta-analyses sampled Black offspring exclusively, a group in which past studies have suggested young motherhood may have a less detrimental effect.70 Regardless, more high-quality research is needed in this area to definitively determine relative risks of internalizing difficulties.
This review should be taken within the context of its limitations. First, whereas grouping analyses by age provides a summary, the analyses include studies with different samples and do not necessarily indicate the expected development of a single individual born to a young mother. Many studies also suffer from attrition, as the offspring of young mothers were more likely to be lost to follow-up than controls. Our search strategy did not capture gray literature, and several included studies examined unique samples that may not be fully generalizable (eg, Morris et al33 ). In addition to sampling constraints, there were limitations in outcome measurement. Thirty of the 73 outcomes (including 27 of the 55 mental health outcomes) were assessed via offspring self-report. Despite having restricted our search to Western countries, there may still be differences between these countries in terms of cultural norms and the resources available to young mothers, and our analysis does not allow us to consider how these differences affect offspring. Furthermore, the breadth of our meta-analyses comes at the expense of having relatively few studies within each. Thus, any conclusions drawn about effect sizes should be considered preliminary.
The relationship between being born to a young mother and experiencing problems with mental health and cognition is likely confounded by several factors, including maternal mental health, socioeconomic background, and the degree to which offspring have access to family support. It is important to elucidate these factors to better understand why the offspring of young mothers are worse off than their peers and to establish a causal link, however this review is limited in its ability to do either given a lack of uniform reporting data on our identified subgroup and sensitivity analyses. Regardless, our review establishes absolute magnitudes of risk in mental health and cognitive functioning by age group and furthers the notion that being born to a young mother is a useful screening criterion for identifying offspring in need of support. We present our hypotheses as to why this effect occurs not to hint at a causal interpretation of our results, but instead to provide avenues for future investigations.
Our understanding of the cognitive and mental health outcomes of the offspring of young mothers could be improved by following up cohorts longitudinally over multiple developmental periods to better understand their trajectories and identify specific periods and targets for prevention and treatment. Studies should also attempt to obtain outcome data from interviews and linking to national registries and other existing large databases. It is crucial for more of this work to include developing countries, considering greater than 90% of adolescent pregnancies occur in these regions.71
Despite its limitations, the present systematic review is the largest synthesis of the outcomes of young mothers’ offspring to date and the first to provide estimates of risk by developmental stage. Although rates of adolescent pregnancy in developed countries have fallen over the past 30 years, young motherhood costs an estimated $9.4 billion annually in the United States alone,72 and early childbearing remains a considerable barrier to the equity of health and opportunity of young mothers and their offspring everywhere.73 Our findings reinforce the importance of prevention efforts but more importantly emphasize the need to monitor these offspring and provide targeted assistance to them and their families. Indeed, it may be beneficial to intervene early, given that this population can fall behind their peers as young as 3 years of age. Supporting the development of young mothers and their offspring is a critical public health goal with potential benefits for these individuals, their families, and society.
Acknowledgments
We thank Jo-Anne Petropoulos for her assistance in developing and refining our search strategies.
Mr Cresswell conceptualized and designed the review, developed the search strategy, designed the data collection instruments, conducted and supervised the study selection and data collection processes, performed analyses, drafted the initial manuscript, and reviewed and revised the manuscript; Mr Faltyn, Ms Lawrence, and Ms Tsai screened studies for inclusion, collected data, and critically revised the manuscript for important intellectual content; Ms Owais developed the search strategy, oversaw the study selection and data collection processes, and critically revised the manuscript for important intellectual content; Mr Savoy supervised the analyses and critically revised the manuscript for important intellectual content; Dr Lipman assisted in conceptualizing and designing the review, and critically revised the manuscript for important intellectual content; Dr Van Lieshout conceptualized and designed the review, resolved disputes that arose during study selection and data collection, and critically revised the manuscript for important intellectual content; and all authors approved the final manuscript as submitted and agree to be accountable for all aspects of the work.
COMPANION PAPER: A companion to this article can be found online at www.peiatrics.org/cgi/doi/10.1542/peds/2022-058142.
FUNDING: No external funding.
CONFLICT OF INTEREST DISCLOSURES: The authors have indicated they have no conflicts of interest to disclose.
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