Parental Age and the Risk of ADHD in Offspring: A Systematic Review and Meta-Analysis
Abstract
:1. Introduction
2. Methods
2.1. Systematic Literature Search
2.2. Study Selection
2.3. Data Extraction
2.4. Quality Assessment
2.5. Data Synthesis and Statistical Analysis
3. Result
3.1. Summary of Literature
3.2. Risk of Child ADHD According to the Lowest Parental Age Category vs. Reference Points
3.3. Risk of Child ADHD According to the Highest Parental Age Category vs. Reference Points
3.4. Dose–Response Meta-Analysis
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Conflicts of Interest
References
- Banaschewski, T.; Becker, K.; Döpfner, M.; Holtmann, M.; Rösler, M.; Romanos, M. Attention-deficit/hyperactivity disorder. Dtsch Arztebl Int. 2017, 114, 149–159. [Google Scholar]
- Thapar, A.; Cooper, M. Attention deficit hyperactivity disorder. Lancet 2016, 387, 1240–1250. [Google Scholar] [CrossRef]
- Childress, A.C.; Stark, J.G. Diagnosis and treatment of attention-deficit/hyperactivity disorder in preschool-aged children. J. Child Adolesc. Psychopharmacol. 2018, 28, 606–614. [Google Scholar] [CrossRef]
- Chhibber, A.; Watanabe, A.H.; Chaisai, C.; Veettil, S.K.; Chaiyakunapruk, N. Global economic burden of attention-deficit/hyperactivity disorder: A systematic review. Pharmacoeconomics 2021, 39, 399–420. [Google Scholar] [CrossRef] [PubMed]
- Thapar, A.; Cooper, M.; Eyre, O.; Langley, K. What have we learnt about the causes of ADHD? J. Child Psychol. Psychiatry Allied Discip. 2013, 54, 3–16. [Google Scholar] [CrossRef] [Green Version]
- Matthews, M.; Nigg, J.T.; Fair, D.A. Attention deficit hyperactivity disorder. Curr. Top. Behav. Neurosci. 2014, 16, 235–266. [Google Scholar]
- Palladino, V.S.; McNeill, R.; Reif, A.; Kittel-Schneider, S. Genetic risk factors and gene-environment interactions in adult and childhood attention-deficit/hyperactivity disorder. Psychiatr. Genet. 2019, 29, 63–78. [Google Scholar] [CrossRef] [Green Version]
- Sciberras, E.; Mulraney, M.; Silva, D.; Coghill, D. Prenatal risk factors and the etiology of ADHD-review of existing evidence. Curr. Psychiatry Rep. 2017, 19, 1. [Google Scholar] [CrossRef]
- Martinez, G.M.; Daniels, K.; Febo-Vazquez, I. Fertility of men and women aged 15–44 in the United States: National survey of family growth, 2011–2015. Natl. Health Stat. Rep. 2018, 113, 1–17. [Google Scholar]
- Walker, K.F.; Thornton, J.G. Advanced maternal age. Obstet. Gynaecol. Reprod. Med. 2016, 26, 354–357. [Google Scholar] [CrossRef]
- Fitzpatrick, K.E.; Tuffnell, D.; Kurinczuk, J.J.; Knight, M. Pregnancy at very advanced maternal age: A UK population-based cohort study. BJOG Int. J. Obstet. Gynaecol. 2017, 124, 1097–1106. [Google Scholar] [CrossRef] [Green Version]
- Luo, D.; Yan, X.; Xu, R.; Zhang, J.; Shi, X.; Ma, J.; Song, Y.; Patton, G.C.; Sawyer, S.M. Chinese trends in adolescent marriage and fertility between 1990 and 2015: A systematic synthesis of national and subnational population data. Lancet Glob. Health 2020, 8, e954–e964. [Google Scholar] [CrossRef]
- Bergh, C.; Pinborg, A.; Wennerholm, U.B. Parental age and child outcomes. Fertil. Steril. 2019, 111, 1036–1046. [Google Scholar] [CrossRef] [PubMed]
- Merikangas, A.K.; Calkins, M.E.; Bilker, W.B.; Moore, T.M.; Gur, R.C.; Gur, R.E. Parental age and offspring psychopathology in the philadelphia neurodevelopmental cohort. J. Am. Acad. Child. Adolesc. Psychiatry 2017, 56, 391–400. [Google Scholar] [CrossRef] [Green Version]
- Wu, S.; Wu, F.; Ding, Y.; Hou, J.; Bi, J.; Zhang, Z. Advanced parental age and autism risk in children: A systematic review and meta-analysis. Acta Psychiatr. Scand. 2017, 135, 29–41. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- McGrath, J.J.; Petersen, L.; Agerbo, E.; Mors, O.; Mortensen, P.B.; Pedersen, C.B. A comprehensive assessment of parental age and psychiatric disorders. JAMA Psychiatry 2014, 71, 301–309. [Google Scholar] [CrossRef]
- Sciberras, E.; Ukoumunne, O.C.; Efron, D. Predictors of parent-reported attention-deficit/hyperactivity disorder in children aged 6–7 years: A national longitudinal study. J. Abnorm. Child Psychol. 2011, 39, 1025–1034. [Google Scholar] [CrossRef] [PubMed]
- Gustafsson, P.; Källén, K. Perinatal, maternal, and fetal characteristics of children diagnosed with attention-deficit-hyperactivity disorder: Results from a population-based study utilizing the Swedish medical birth register. Dev. Med. Child Neurol. 2011, 53, 263–268. [Google Scholar] [CrossRef]
- Kim, K.M.; Choi, Y.J.; Lim, M.H.; Ha, M.; Kwon, H.J. Parental age at childbirth and risk for attention-deficit/hyperactivity disorder in offspring. J. Psychiatr. Res. 2020, 131, 180–186. [Google Scholar] [CrossRef] [PubMed]
- Chudal, R.; Joelsson, P.; Gyllenberg, D.; Lehti, V.; Leivonen, S.; Hinkka-Yli-Salomäki, S.; Gissler, M.; Sourander, A. Parental age and the risk of attention-deficit/hyperactivity disorder: A nationwide, population-based cohort study. J. Am. Acad Child. Adolesc Psychiatry 2015, 54, 487–494.e1. [Google Scholar] [CrossRef]
- Janecka, M.; Hansen, S.N.; Modabbernia, A.; Browne, H.A.; Buxbaum, J.D.; Schendel, D.E.; Reichenberg, A.; Parner, E.T.; Grice, D.E. Parental age and differential estimates of risk for neuropsychiatric disorders: Findings from the danish birth cohort. J. Am. Acad. Child Adolesc. Psychiatry 2019, 58, 618–627. [Google Scholar] [CrossRef] [PubMed]
- Hvolgaard Mikkelsen, S.; Olsen, J.; Bech, B.H.; Obel, C. Parental age and attention-deficit/hyperactivity disorder (ADHD). Int. J. Epidemiol. 2017, 46, 409–420. [Google Scholar] [CrossRef] [Green Version]
- Chang, Z.; Lichtenstein, P.; D’Onofrio, B.M.; Almqvist, C.; Kuja-Halkola, R.; Sjölander, A.; Larsson, H. Maternal age at childbirth and risk for ADHD in offspring: A population-based cohort study. Int. J. Epidemiol. 2014, 43, 1815–1824. [Google Scholar] [CrossRef] [PubMed]
- Silva, D.; Colvin, L.; Hagemann, E.; Bower, C. Environmental risk factors by gender associated with attention-deficit/hyperactivity disorder. Pediatrics 2014, 133, e14–e22. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Galera, C.; Cote, S.M.; Bouvard, M.P.; Pingault, J.-B.; Melchior, M.; Michel, G.; Boivin, M.; Tremblay, R.E. Early risk factors for hyperactivity-impulsivity and inattention trajectories From age 17 months to 8 years. Arch. Gen. Psychiatry 2011, 68, 1267–1275. [Google Scholar] [CrossRef] [Green Version]
- Sauver, J.L.S.; Barbaresi, W.J.; Katusic, S.K.; Colligan, R.C.; Weaver, A.L.; Jacobsen, S.J. Early life risk factors for attention-dericit/hyperactivity disorder: A population-based cohort study. Mayo Clin. Proc. 2004, 79, 1124–1131. [Google Scholar] [CrossRef]
- Wang, X.; Martinez, M.P.; Chow, T.; Walthall, J.C.; Guber, K.M.; Xiang, A.H. Attention-deficit hyperactivity disorder risk: Interaction between parental age and maternal history of attention-deficit hyperactivity disorder. J. Dev. Behav. Pediatrics 2019, 40, 321–329. [Google Scholar] [CrossRef]
- Halmøy, A.; Klungsøyr, K.; Skjærven, R.; Haavik, J. Pre- and perinatal risk factors in adults with attention-deficit/hyperactivity disorder. Biol. Psychiatry 2012, 71, 474–481. [Google Scholar] [CrossRef]
- Hinshaw, S.P. Attention deficit hyperactivity disorder (ADHD): Controversy, developmental mechanisms, and multiple levels of analysis. Annu. Rev. Clin. Psychol. 2018, 14, 291–316. [Google Scholar] [CrossRef] [Green Version]
- Chudal, R.; Gissler, M.; Sucksdorff, D.; Lehti, V.; Suominen, A.; Hinkka-Yli-Salomäki, S.; Brown, A.S.; Sourander, A. Parental age and the risk of bipolar disorders. Bipolar Disord. 2014, 16, 624–632. [Google Scholar] [CrossRef]
- Durkin, M.S.; Maenner, M.J.; Newschaffer, C.J.; Lee, L.C.; Cunniff, C.M.; Daniels, J.L.; Kirby, R.S.; Leavitt, L.; Miller, L.; Zahorodny, W.; et al. Advanced parental age and the risk of autism spectrum disorder. Am. J. Epidemiol 2008, 168, 1268–1276. [Google Scholar] [CrossRef] [Green Version]
- Moher, D.; Liberati, A.; Tetzlaff, J.; Altman, D.G.; Group, P. Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. PLoS Med. 2009, 6, e1000097. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Wells, G.A.; Shea, B.; O’Connell, D.; Peterson, J.; Robertson, J.; Welch, V.; Losos, M.; Tugwell, P. The Newcastle-Ottawa Scale (NOS) for Assessing the Quality of Nonrandomised Studies in Meta-Analyses. Available online: http://www.ohri.ca/programs/clinical_epidemiology/oxford.asp (accessed on 9 November 2020).
- Lau, J.; Ioannidis, J.P.; Terrin, N.; Schmid, C.H.; Olkin, I. The case of the misleading funnel plot. BMJ Clin. Res. Ed. 2006, 333, 597–600. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Greenland, S.; Longnecker, M.P. Method for trend estimation from summarized doseresponse data. Am. J. Epidemiol. 1992, 135, 1301–1309. [Google Scholar] [CrossRef]
- Orsini, N.; Bellocco, R.; Greenland, S. Generalized least squares for trend estimation of summarized dose–response data. Stata J. 2006, 6, 40–57. [Google Scholar] [CrossRef] [Green Version]
- Orsini, N.; Li, R.; Wolk, A.; Khudyakov, P.; Spiegelman, D. Meta-analysis for linear and nonlinear dose-response relations: Examples, an evaluation of approximations, and software. Am. J. Epidemiol. 2012, 175, 66–73. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Maitra, S.; Mukhopadhyay, K. Parental age and developmental milestones: Pilot study indicated a role in understanding ADHD severity in Indian probands. BMC Pediatrics 2019, 19, 117. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Keown, L. Fathering and mothering of preschool boys with hyperactivity. Int. J. Behav. Dev. 2011, 35, 161–168. [Google Scholar] [CrossRef]
- Amiri, S.; Malek, A.; Sadegfard, M.; Abdi, S. Pregnancy-related maternal risk factors of attention-deficit hyperactivity disorder: A case-control study. Int. Sch. Res. Not. 2012, 2012, 458064. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Gurevitz, M.; Geva, R.; Varon, M.; Leitner, Y. Early markers in infants and toddlers for development of ADHD. J. Atten. Disord. 2014, 18, 14–22. [Google Scholar] [CrossRef]
- Ghanizadeh, A. Association of ADHD symptoms severity with higher paternal and lower maternal age of a clinical sample of children. Acta Med. Iran. 2014, 52, 49–51. [Google Scholar]
- Talge, N.M.; Allswede, D.M.; Holzman, C. Gestational age at term, delivery circumstance, and their association with childhood attention deficit hyperactivity disorder symptoms. Paediatr. Perinat. Epidemiol. 2016, 30, 171–180. [Google Scholar] [CrossRef] [PubMed]
- Claycomb, C.D.; Ryan, J.J.; Miller, L.J.; Schnakenberg-Ott, S.D. Relationships among attention deficit hyperactivity disorder, induced labor, and selected physiological and demographic variables. J. Clin. Psychol. 2004, 60, 689–693. [Google Scholar] [CrossRef]
- Homan, K.J.; Barbaresi, W.J.; Mellon, M.W.; Weaver, A.L.; Killian, J.M.; Lucchetti, A.R.; Katusic, S.K. Psychiatric disorders in mothers of children with attention-deficit/hyperactivity disorder: A population-based perspective. J. Child Fam. Stud. 2019, 28, 1042–1051. [Google Scholar] [CrossRef]
- Wüstner, A.; Otto, C.; Schlack, R.; Hölling, H.; Klasen, F.; Ravens-Sieberer, U. Risk and protective factors for the development of ADHD symptoms in children and adolescents: Results of the longitudinal BELLA study. PLoS ONE 2019, 14, e0214412. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Huhdanpaa, H.; Morales-Munoz, I.; Aronen, E.T.; Polkki, P.; Saarenpaa-Heikkila, O.; Kylliainen, A.; Paavonen, E.J. Prenatal and postnatal predictive factors for children’s inattentive and hyperactive symptoms at 5 years of age: The role of early family-related factors. Child Psychiatry Hum. Dev. 2020. [Google Scholar] [CrossRef]
- Sandin, S.; Hultman, C.M.; Kolevzon, A.; Gross, R.; MacCabe, J.H.; Reichenberg, A. Advancing maternal age is associated with increasing risk for autism: A review and meta-analysis. J. Am. Acad. Child Adolesc. Psychiatry 2012, 51, 477–486.e1. [Google Scholar] [CrossRef]
- Joelsson, P.; Chudal, R.; Uotila, J.; Suominen, A.; Sucksdorff, D.; Gyllenberg, D.; Sourander, A. Parental psychopathology and offspring attention-deficit/hyperactivity disorder in a nationwide sample. J. Psychiatr. Res. 2017, 94, 124–130. [Google Scholar] [CrossRef]
- Agnafors, S.; Bladh, M.; Svedin, C.G.; Sydsjö, G. Mental health in young mothers, single mothers and their children. BMC Psychiatry 2019, 19, 112. [Google Scholar] [CrossRef] [Green Version]
- Deault, L.C. A systematic review of parenting in relation to the development of comorbidities and functional impairments in children with attention-deficit/hyperactivity disorder (ADHD). Child Psychiatry Hum. Dev. 2010, 41, 168–192. [Google Scholar] [CrossRef]
- Sansone, A.; Di Dato, C.; De Angelis, C.; Menafra, D.; Pozza, C.; Pivonello, R.; Isidori, A.; Gianfrilli, D. Smoke, alcohol and drug addiction and male fertility. Reprod. Biol. Endocrinol. 2018, 16, 3. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Russell, G.; Ford, T.; Rosenberg, R.; Kelly, S. The association of attention deficit hyperactivity disorder with socioeconomic disadvantage: Alternative explanations and evidence. J. Child Psychol. Psychiatry Allied Discip. 2014, 55, 436–445. [Google Scholar] [CrossRef] [Green Version]
- Lugo-Candelas, C.; Corbeil, T.; Wall, M.; Posner, J.; Bird, H.; Canino, G.; Fisher, P.W.; Suglia, S.F.; Duarte, C.S. ADHD and risk for subsequent adverse childhood experiences: Understanding the cycle of adversity. J. Child Psychol. Psychiatry Allied Discip. 2020. [Google Scholar] [CrossRef] [PubMed]
- Vohr, B.R.; Davis, P.E.; Wanke, C.A.; Krebs, N.F. Neurodevelopment: The impact of nutrition and inflammation during preconception and pregnancy in low-resource settings. Pediatrics 2017, 139, S38–S49. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Partridge, S.; Balayla, J.; Holcroft, C.A.; Abenhaim, H.A. Inadequate prenatal care utilization and risks of infant mortality and poor birth outcome: A retrospective analysis of 28,729,765 U.S. deliveries over 8 years. Am. J. Perinatol. 2012, 29, 787–793. [Google Scholar] [CrossRef]
- Londero, A.P.; Rossetti, E.; Pittini, C.; Cagnacci, A.; Driul, L. Maternal age and the risk of adverse pregnancy outcomes: A retrospective cohort study. BMC Pregnancy Childbirth 2019, 19, 261. [Google Scholar] [CrossRef]
- Ask, H.; Gustavson, K.; Ystrom, E.; Havdahl, K.A.; Tesli, M.; Askeland, R.B.; Reichborn-Kjennerud, T. Association of gestational age at birth with symptoms of attention-deficit/hyperactivity disorder in children. JAMA Pediatrics 2018, 172, 749–756. [Google Scholar] [CrossRef]
- Hultman, C.M.; Torrång, A.; Tuvblad, C.; Cnattingius, S.; Larsson, J.O.; Lichtenstein, P. Birth weight and attention-deficit/hyperactivity symptoms in childhood and early adolescence: A prospective Swedish twin study. J. Am. Acad. Child Adolesc. Psychiatry 2007, 46, 370–377. [Google Scholar] [CrossRef]
- Deater-Deckard, K. Parents’ and children’s ADHD in a family system. J. Abnorm. Child Psychol. 2017, 45, 519–525. [Google Scholar] [CrossRef]
- Lehti, V.; Niemelä, S.; Heinze, M.; Sillanmäki, L.; Helenius, H.; Piha, J.; Kumpulainen, K.; Tamminen, T.; Almqvist, F.; Sourander, A. Childhood predictors of becoming a teenage mother among finnish girls. Acta Obstet. Gynecol. Scand. 2012, 91, 1319–1325. [Google Scholar] [CrossRef] [PubMed]
- Besag, F.M. ADHD treatment and pregnancy. Drug Saf. 2014, 37, 397–408. [Google Scholar] [CrossRef] [PubMed]
- Hosain, G.M.; Berenson, A.B.; Tennen, H.; Bauer, L.O.; Wu, Z.H. Attention deficit hyperactivity symptoms and risky sexual behavior in young adult women. J. Women Health 2012, 21, 463–468. [Google Scholar] [CrossRef] [Green Version]
- Rieske, R.D.; Matson, J.L. Parental age at conception and the relationship with severity of autism symptoms. Dev. Neurorehabilit. 2020, 23, 265–270. [Google Scholar] [CrossRef] [PubMed]
- Brown, A.; Bao, Y.; McKeague, I.; Shen, L.; Schaefer, C. Parental age and risk of bipolar disorder in offspring. Psychiatry Res. 2013, 208, 225–231. [Google Scholar] [CrossRef] [Green Version]
- Goldmann, J.M.; Wong, W.S.; Pinelli, M.; Farrah, T.; Bodian, D.; Stittrich, A.B.; Glusman, G.; Vissers, L.E.; Hoischen, A.; Roach, J.C.; et al. Parent-of-origin-specific signatures of de novo mutations. Nat. Genet. 2016, 48, 935–939. [Google Scholar] [CrossRef]
- Pedersen, C.B.; McGrath, J.; Mortensen, P.B.; Petersen, L. The importance of father’s age to schizophrenia risk. Mol. Psychiatry 2014, 19, 530–531. [Google Scholar] [CrossRef] [PubMed]
- Sharma, R.; Agarwal, A.; Rohra, V.K.; Assidi, M.; Abu-Elmagd, M.; Turki, R.F. Effects of increased paternal age on sperm quality, reproductive outcome and associated epigenetic risks to offspring. Reprod. Biol. Endocrinol. 2015, 13, 35. [Google Scholar] [CrossRef] [Green Version]
- Sanders, S.J.; Murtha, M.T.; Gupta, A.R.; Murdoch, J.D.; Raubeson, M.J.; Willsey, A.J.; Ercan-Sencicek, A.G.; DiLullo, N.M.; Parikshak, N.N.; Stein, J.L.; et al. De novo mutations revealed by whole-exome sequencing are strongly associated with autism. Nature 2012, 485, 237–241. [Google Scholar] [CrossRef] [PubMed]
- Attali, E.; Yogev, Y. The impact of advanced maternal age on pregnancy outcome. Best Pract. Res. Clin. Obstet. Gynaecol. 2021, 70, 2–9. [Google Scholar] [CrossRef]
- Koshida, S.; Arima, H.; Fujii, T.; Ito, Y.; Murakami, T.; Takahashi, K. Impact of advanced maternal age on adverse infant outcomes: A Japanese population-based study. Eur. J. Obstet. Gynecol. Reprod. Biol. 2019, 242, 178–181. [Google Scholar] [CrossRef]
- Sutcliffe, A.G.; Barnes, J.; Belsky, J.; Gardiner, J.; Melhuish, E. The health and development of children born to older mothers in the United Kingdom: Observational study using longitudinal cohort data. BMJ Clin. Res. Ed. 2012, 345, e5116. [Google Scholar] [CrossRef] [PubMed] [Green Version]
Study | Study Site | Study Design | n | Number with ADHD in Study | Outcome | Diagnostic Method | Type of Adjusted Factors a | |||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
Gender | SES | Psyc. History | Prenatal | Parental Age | Exposure | |||||||
Chang et al. (2014) [23] | Sweden | Cohort | 1,495,543 | 30,674 | ADHD | ICD–10 | ✓ | ✓ | ✓ | |||
Chudal R. et al. (2015) [20] | Finland | Case-control | 49,534 | 10,409 | ADHD | ICD–10 | ✓ | ✓ | ✓ | ✓ | ✓ | |
Galera et al. (2011) [25] | Canada | cohort | 2057 | 330 | ADHD | DSM–IV | ✓ | ✓ | ✓ | ✓ | ✓ | |
Gustafsson et al. (2011) [18] | Sweden | Case-control | 32,012 | 237 | ADHD | DSM–III–R, DSM–IV | ✓ | ✓ | ✓ | |||
Hvolgaard et al. (2017) [22] | Danish | Sibling cohort | 943,785 | 12,294 | ADHD | ICD–10 | ✓ | ✓ | ✓ | ✓ | ||
Janecka et al. (2019) [21] | Danish | Cohort | 1,490,745 | 25,307 | ADHD | ICD–10 | ✓ | ✓ | ✓ | ✓ | ||
Kim et al. (2020) [19] | Korea | Case-control | 28,973 | 2112 | ADHD | K–ARS | ✓ | ✓ | ✓ | ✓ | ||
Sauver et al. (2004) [26] | America | Case-control | 5701 | 305 | ADHD | DSM–IV | ✓ | ✓ | ✓ | |||
Sciberras et al. (2011) [17] | Australia | Cohort | 4464 | 57 | ADHD | DSM–IV | ||||||
Silva et al. (2014) [24] | Australia | Case-control | 43,062 | 12,991 | ADHD | DSM–IV | ||||||
Wang et al. (2019) [27] | America | Cohort | 321,272 | 16,385 | ADHD | DSM–IV | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ |
Maternal | Paternal | |||||
---|---|---|---|---|---|---|
Subgroup Analysis | n | OR (95% CI) | Heterogeneity (I2, p) | n | OR (95% CI) | Heterogeneity (I2, p) |
Lowest vs. referred (crude) | ||||||
Design | ||||||
Case-control | 4 | 1.94 (1.26, 2.99) | I2 = 96.4%, p < 0.001 | 3 | 2.44 (1.30, 4.57) | I2 = 85.4%, p = 0.001 |
Cohort | 5 | 1.96 (1.41, 2.73) | I2 = 98.4%, p < 0.001 | 3 | 1.93 (1.22, 3.05) | I2 = 98.8%, p < 0.001 |
Geographical area | ||||||
Europe | 3 | 2.57 (2.32, 2.85) | I2 = 85.8%, p = 0.001 | 3 | 2.74 (2.28, 3.29) | I2 = 88.0%, p < 0.001 |
America | 3 | 1.35 (0.85, 2.14) | I2 = 87.3%, p < 0.001 | 2 | 1.20 (1.09, 1.32) | I2 = 0%, p = 0.97 |
Asia and Oceania | 3 | 2.02 (1.38, 2.96) | I2 = 77.5%, p = 0.012 | 1 | 2.89 (1.74, 4.80) | |
Diagnostic method | ||||||
ICD–10 | 4 | 2.58 (2.34, 2.83) | I2 = 79.0%, p = 0.003 | 4 | 2.75 (2.32, 3.26) | I2 = 82.3%, p = 0.001 |
DSM–IV | 5 | 1.48 (1.12, 1.94) | I2 = 90.4%, p < 0.001 | 2 | 1.20 (1.09, 1.32) | I2 = 0%, p = 0.97 |
Lowest vs. referred (adjusted) | ||||||
Design | ||||||
Case-control | 5 | 1.52 (1.15, 2.01) | I2 = 98.3%, p < 0.001 | 3 | 1.48 (0.84, 2.62) | I2 = 65.3%, p = 0.056 |
Cohort | 3 | 1.41 (0.90, 2.21) | I2 = 81.5%, p = 0.005 | 3 | 1.90 (1.31, 2.75) | I2 = 97.9%, p < 0.001 |
Geographical area | ||||||
Europe | 4 | 1.52 (1.08, 2.13) | I2 = 98.6%, p < 0.001 | 3 | 2.22 (1.96, 2.52) | I2 = 66.3%, p = 0.051 |
America | 3 | 1.27 (0.93, 1.75) | I2 = 63.6%, p = 0.066 | 2 | 1.02 (0.51, 2.03) | I2 = 55.5%, p = 0.134 |
Asia and Oceania | 1 | 2.19 (1.57, 3.05) | 1 | 0.36 (1.36, 4.09) | ||
Diagnostic method | ||||||
ICD–10 | 5 | 1.62 (1.19, 2.20) | I2 = 98.2%, p < 0.001 | 4 | 2.24 (2.01, 2.51) | I2 = 49.5%, p = 0.115 |
DSM–IV | 3 | 1.27 (0.93, 1.75) | I2 = 63.3%, p = 0.066 | 2 | 1.02 (0.51, 2.03) | I2 = 55.5%, p = 0.134 |
Highest vs. referred (crude) | ||||||
Design | ||||||
Case-control | 4 | 1.08 (0.90, 1.30) | I2 = 57.8%, p = 0.068 | 3 | 1.20 (0.89, 1.63) | I2 = 76.3%, p = 0.015 |
Cohort | 3 | 0.94 (0.77, 1.15) | I2 = 69.7%, p = 0.037 | 2 | 0.87 (0.71, 1.07) | I2 = 95.2%, p < 0.001 |
Geographical area | ||||||
Europe | 3 | 0.95 (0.81, 1.13) | I2 = 77.4%, p = 0.012 | 3 | 0.90 (0.75, 1.07) | I2 = 90.9%, p < 0.001 |
America | 1 | 1.11 (0.80, 1.54) | 1 | 1.07 (0.84, 1.36) | ||
Asia and Oceania | 3 | 1.13 (0.82, 1.56) | I2 = 71.0%, p = 0.032 | 1 | 1.65 (1.27, 2.15) | |
Diagnostic method | ||||||
ICD–10 | 4 | 1.05 (0.85, 1.30) | I2 = 83.6%, p < 0.001 | 4 | 1.02 (0.83, 1.26) | I2 = 93.5%, p < 0.001 |
DSM–IV | 3 | 1.00 (0.87, 1.14) | I2 = 0%, p = 0.726 | 1 | 1.07 (0.84, 1.36) | |
Highest vs. referred (adjusted) | ||||||
Design | ||||||
Case-control | 3 | 1.10 (0.72, 1.67) | I2 = 78.2%, p = 0.010 | 3 | 1.20 (0.95, 1.51) | I2 = 0%, p = 0.548 |
Cohort | 2 | 1.12 (0.54, 2.30) | I2 = 97.4%, p < 0.001 | 2 | 0.73 (0.51, 1.05) | I2 = 98.3%, p < 0.001 |
Geographical area | ||||||
Europe | 3 | 0.99 (0.65, 1.51) | I2 = 94.8%, p < 0.001 | 3 | 0.81 (0.59, 1.10) | I2 = 96.7%, p < 0.001 |
America | 1 | 1.11 (0.80, 1.54) | 1 | 1.99 (0.70, 5.64) | ||
Asia and Oceania | 1 | 1.82 (1.05, 3.16) | 1 | 1.22 (0.90, 1.65) | ||
Diagnostic method | ||||||
ICD–10 | 4 | 1.11 (0.75, 1.65) | I2 = 93.4%, p < 0.001 | 4 | 0.88 (0.66, 1.18) | I2 = 95.8%, p < 0.001 |
DSM–IV | 1 | 1.11 (0.80, 1.54) | 1 | 1.99 (0.70, 5.64) |
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Min, X.; Li, C.; Yan, Y. Parental Age and the Risk of ADHD in Offspring: A Systematic Review and Meta-Analysis. Int. J. Environ. Res. Public Health 2021, 18, 4939. https://doi.org/10.3390/ijerph18094939
Min X, Li C, Yan Y. Parental Age and the Risk of ADHD in Offspring: A Systematic Review and Meta-Analysis. International Journal of Environmental Research and Public Health. 2021; 18(9):4939. https://doi.org/10.3390/ijerph18094939
Chicago/Turabian StyleMin, Xianying, Chao Li, and Yan Yan. 2021. "Parental Age and the Risk of ADHD in Offspring: A Systematic Review and Meta-Analysis" International Journal of Environmental Research and Public Health 18, no. 9: 4939. https://doi.org/10.3390/ijerph18094939
APA StyleMin, X., Li, C., & Yan, Y. (2021). Parental Age and the Risk of ADHD in Offspring: A Systematic Review and Meta-Analysis. International Journal of Environmental Research and Public Health, 18(9), 4939. https://doi.org/10.3390/ijerph18094939