{"paper_id":"3d5f3c35-4e93-495c-9cd0-385220a0f9ad","body_text":"Setting a research agenda for examining early risk for elevated cognitive disengagement syndrome symptoms using data from the ABCD cohort | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Setting a research agenda for examining early risk for elevated cognitive disengagement syndrome symptoms using data from the ABCD cohort Kelsey K. Wiggs, Taryn E. Cook, Isha Lodhawala, Emma N. Cleary, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4468007/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 10 Mar, 2025 Read the published version in European Child & Adolescent Psychiatry → Version 1 posted 9 You are reading this latest preprint version Abstract Background. Little research has examined early life risk for symptoms of cognitive disengagement syndrome (CDS) despite a well-established literature regarding co-occurring outcomes (e.g., attention-deficit/hyperactivity disorder). The current study estimated bivariate associations between early life risk factors and CDS in a large and representative sample of U.S. children. Methods. We conducted secondary analyses of baseline data from the Adolescent Brain Cognitive Development (ABCD) study (N = 8,096 children, 9–10 years old). Birthing parents reported early life risk factors on a developmental history questionnaire, including parental, prenatal, delivery and birth, and developmental milestone information. They also completed the Child Behavior Checklist, which includes a CDS subscale that was dichotomized to estimate the odds of elevated CDS symptoms (i.e., T- score > 70) in children related to risk indices. Results. We observed significantly elevated odds of CDS related to parental risk factors (i.e., unplanned pregnancy, pregnancy awareness after 6 weeks, teenage parenthood), birthing parent illnesses in pregnancy (i.e., severe nausea, proteinuria, pre-eclampsia/toxemia, severe anemia, urinary tract infection), pregnancy complications (i.e., bleeding), prenatal substance exposures (i.e., prescription medication, tobacco, illicit drugs), delivery and birth risk factors (i.e., child blue at delivery, child not breathing, jaundice, incubation after delivery), and late motor and speech milestones in children. Conclusions. Several early-life risk factors were associated with elevated odds of CDS at ages 9–10 years; study design prevents the determination of causality. Further investigation is warranted regarding early life origins of CDS with priority given to risk indices that have upstream commonalities (i.e., that restrict fetal growth, nutrients, and oxygen). prenatal risk perinatal risk early life risk cognitive disengagement syndrome sluggish cognitive tempo Figures Figure 1 Figure 2 Figure 3 Introduction Research examining the developmental origins of health and disease hypothesis and/or the prenatal programming hypothesis has demonstrated a wide range of health outcomes in childhood and adulthood are rooted in prenatal and early life experiences [ 1 – 4 ], including neurodevelopmental outcomes (e.g., attention-deficit/hyperactivity disorder [ADHD]) [ 4 ]. Although researchers are still pursuing which pre- and perinatal risk factors cause outcomes [ 5 , 6 ], certain genetic and environmental risk factors are likely to predispose the developing brain to neurodivergence (e.g., ADHD, autism spectrum disorders [ASD]) generally [ 7 – 10 ], while others may specify ultimate developmental outcomes [ 7 , 10 ]. Cognitive disengagement syndrome (CDS; previously called sluggish cognitive tempo [SCT]) co-occurs in up to 40% of children with ADHD [ 11 – 14 ]. This may suggest etiologic overlap, yet very little is known about the early life origins of CDS [ 12 ]. First studied in the 1980s, CDS is characterized by internally-focused distraction (e.g., excessive daydreaming, zoning out), mental confusion, and hypo-activity (e.g., lethargy, drowsiness) [ 15 , 16 ] .In early factor analytic studies, CDS emerged as a third dimension of ADHD alongside inattentive and hyperactive-impulsive dimensions [ 15 , 16 ], though it is still debated whether CDS should be considered a presentation of ADHD, its own disorder, or a transdiagnostic phenotypic trait [ 12 , 17 , 18 ]. Furthermore, CDS is related to difficulties (e.g., academic, social, and mental health) beyond what is accounted for by ADHD symptoms alone [ 12 ]. Only three studies have examined prenatal risk for CDS [ 19 – 21 ]. Two studies have examined the association between prenatal alcohol exposure and CDS, finding opposing results [ 19 , 20 ]. Graham et al. [ 19 ] found higher mean scores measured by a 15-item CDS scale among children 8–16 exposed prenatally to heavy alcohol use [ 19 ]. However, in a more recent study comparing children ages 7.5–9.5 with and without fetal alcohol spectrum disorders, there were no differences between groups regarding the odds of having a CDS score in the “borderline” or “clinical” range (i.e., T -score ≥ 65) on the Child Behavior Checklist (CBCL) or Teacher’s Report Form (TRF) [ 20 ]. There are many possible reasons for these discrepant findings, including that only 12 children had elevated CDS symptoms in the more recent study [ 20 ], which limits statistical power. Finally, Comprodon-Rosanas et al. [ 21 ] observed an association between prenatal tobacco exposure and “borderline” or “clinically” elevated CDS scores measured by the CBCL among children ages 7–10, though the association was no longer significant after adjustment for covariates; it should again be noted that only 20 children were observed to have elevated CDS symptoms [ 21 ]. In addition to these prenatal studies, there has been one study each documenting an association between extremely low birth weight [ 22 ] and iron deficiency [ 23 ] in infants with subsequent CDS symptoms in youth. Identification of early life risk factors for CDS is important because findings regarding common (e.g., to CDS and ADHD) and unique etiologic risk factors may 1) shape ongoing debate and decisions regarding whether CDS is best conceptualized as a distinct phenomenon or as a presentation of ADHD [ 12 ], 2) influence prevention and intervention efforts, and 3) guide theory regarding CDS more broadly. The aim of this study was to examine the magnitude of bivariate associations, in a far larger sample than prior literature, to illuminate which risk factors may be most important to prioritize in future investigations. Methods Data Source We conducted a secondary analysis of baseline data from the Adolescent Brain Cognitive Development (ABCD) study, which was considered exempt from Institutional Review Board approval. The ABCD study is a prospective, representative twenty-two site study of U.S. children [ 24 ]. Baseline data were collected from 2017 to 2018, when children were roughly 9–10 years old. We used data from Release 4.0 in the current study ( 10.15154/bkya-7b87 ). Participant recruitment procedures are described elsewhere [ 25 ]. Sample The ABCD study (N = 11,878) did not include children that were born extremely premature (i.e., born at less than 28 weeks of gestation). For our study, we excluded children who did not have a Developmental History Questionnaire (exposures) completed by their biological mother/birthing parent (n = 1,797), as—like other researchers who have used these data—we anticipated particular difficulty in recall for other caregivers [ 26 , 27 ]. Next, we excluded children without valid reported birth weight (n = 3), multiples (n = 1,976) [ 28 , 29 ], and children with missing multiples status (n = 4) [ 28 – 31 ]. Finally, we excluded two children without information on the outcome (see Measures), resulting in a final sample of 8,096 children. We present information on age, sex, and race/ethnicity in Table 1 . Of note, from here onward we use the terms birthing parent and other parent to refer to female and male parents, respectively, as we did not have information on gender identity. Table 1 Child Demographics Stratified by CDS Group No CDS Elevation ( T -score > 70; n = 7881) CDS Elevation ( T -Score ≥ 70; n = 215) Mean (SD) Mean (SD) Age at Research Visit 118.51 (7.57) months 118.40 (7.70) months n (%) n (%) Sex Assigned at Birth Female 3786 (48.04) 83 (38.60) Male 4095 (51.96) 132 (61.39) Race Asian 481 (6.10) 12 (5.58) Black 1673 (21.23) 67 (31.16) Native/Indigenous Alaskan or American 266 (3.38) 11 (5.12) Native Hawaiian or Pacific Islander 44 (0.56) 4 (1.86) White 5811 (73.73) 144 (66.98) Other 574 (7.28) 25 (11.63) Unknown 119 (1.51) 1 (0.47) Hispanic/Latiné 22 (0.28) 1 (0.47) Note CDS = cognitive disengagement syndrome (termed ‘sluggish cognitive tempo’ on the Child Behavior Checklist scale used to define the construct in this study). Measures Exposures. We only excluded variables that we believed would be especially susceptible to recall difficulties (e.g., exact ages in months when developmental milestones occurred, dose/frequency of medication and drug use), outside the scope of the current study (e.g., vitamin use), and that were deemed too rare in frequency (i.e., rubella and convulsions in pregnancy). We present the frequencies and percentages of children exposed among the total sample and the elevated CDS group in Table 2 . We report on frequency of missing for each variable below. Table 2 Exposure Frequencies Among Total Sample, Elevated CDS Sample, and Odds Ratios Estimating Associations between Exposures and CDS Total Sample (N = 8,096) CDS Elevation ( T -Score ≥ 70; n = 215) n (%) n (%) Odds Ratio (95% CI) Parental Risk Factors Unplanned Pregnancy 3,260 (40.27) 111 (51.63) 1.60 (1.22–2.10) Pregnancy Awareness after 6 Weeks 2,248 (24.77) 77 (35.81) 1.47 (1.11–1.95) Teen Birthing Parent 549 (6.78) 26 (12.09) 1.93 (1.27–2.93) Birthing Parent Age of 40+ 348 (4.30) 7 (3.26) 0.74 (0.35–1.59) Teen Other Parent 292 (3.61) 14 (6.51) 1.90 (1.09–3.32) Other Parent Age of 45+ 290 (3.58) 8 (3.72) 1.04 (0.51–2.13) Birthing Parent Illness in Pregnancy Severe Nausea 1,125 (13.90) 56 (26.05) 2.28 (1.67–3.12) Gestational Hypertension 678 (8.38) 23 (10.70) 1.35 (0.87–2.10) Persistent Proteinuria 35 (0.43) 7 (3.26) 9.53 (4.12–22.07) Preeclampsia/Toxemia 448 (5.53) 22 (10.23) 2.02 (1.29–3.17) Gestational Diabetes 535 (6.61) 16 (7.44) 1.15 (0.69–1.94) Severe Gall Bladder Attack 96 (1.19) 5 (2.33) 2.05 (0.83–5.11) Severe Anemia 338 (4.18) 20 (9.30) 2.48 (1.54–2.98) Urinary Tract Infection 645 (7.97) 37 (17.21) 2.51 (1.75–3.62) Any other condition requiring medical care 552 (6.82) 15 (6.98) 1.03 (0.61–1.76) Pregnancy Complications Heavy Bleeding 253 (3.13) 16 (7.44) 2.60 (1.54–4.40) Placental Problems 209 (2.58) 6 (2.79) 1.10 (0.48–2.50) Birth Parent Accident/Injury Requiring Medical Care 151 (1.87) 5 (2.33) 1.27 (0.51–2.13) RH Incompatibility 230 (2.84) 7 (3.26) 1.18 (0.55–2.53) Prenatal Substance Exposure Prescription Medication 1,236 (15.27) 48 (22.33) 1.62 (1.17–2.25) Tobacco 1,082 (13.37) 48 (22.33) 1.90 (1.37–2.64) Alcohol 2,043 (25.23) 59 (27.44) 1.12 (0.83–1.52) Illicit Drugs 601 (7.42) 39 (18.14) 2.89 (2.02–4.13) Delivery and Birth Prematurity 818 (10.10) 22 (10.23) 1.02 (0.65–1.60) Low Birth Weight 755 (9.33) 20 (9.30) 0.97 (0.63–1.59) C-section 2,488 (30.73) 62 (28.84) 0.91 (0.68–1.23) Blue at Birth 241 (2.98) 15 (6.98) 2.57 (1.49–4.41) Did not Breath at First 335 (4.14) 17 (7.90) 2.10 (1.26–3.49) Required Oxygen 475 (5.87) 17 (7.90) 1.40 (0.85–2.32) Slow Heartbeat 218 (2.69) 10 (4.65) 1.80 (0.94–3.46) Jaundice Requiring Treatment 1,192 (14.72) 51 (23.72) 1.88 (1.36–2.59) Required Blood Transfusion 26 (0.32) 2 (0.93) 3.07 (0.72–13.07) Incubated after Delivery 725 (8.96) 29 (13.49) 1.68 (1.13–2.51) Developmental Milestones Late Motor Development 599 (7.40) 36 (16.74) 2.61 (1.81–3.78) Late Speech Development 1,276 (15.76) 68 (31.63) 2.56 (1.91–3.43) Note CDS = cognitive disengagement syndrome. Parental Risk Factors. Birthing parents reported on whether their pregnancy was planned (missing n = 47, 0.58%), when they became aware they were pregnant (missing n = 514, 6.35%), their age and the age of the other biological parent when their child was born (missing n = 66, 0.82%; missing n = 281, 3.47%; respectively). Because unplanned pregnancies may confer risk to embryonic and fetal development (e.g., via lack of prenatal care in absence of pregnancy awareness) [ 32 ] and serve as an indication of broader environmental risk [ 32 ], we created an indicator variable for unplanned pregnancy. We also created an indicator variable for pregnancy awareness after 6 weeks of gestation, which is after the observed median in our data (5 weeks) and also after the mean (5.5 weeks) observed in other research [ 33 , 34 ]. Finally, we dichotomized parental age variables in two ways based on prior literature demonstrating a parabolic pattern of risk for adverse outcomes in children [ 34 – 37 ], including risk for ADHD [ 38 ]: teenage (i.e., under 20) and advanced age (i.e., 40 + years for birthing parents and 45 + years for other biological parent). Prenatal Risk: Birthing Parent Illness, Pregnancy Complications, and Substance Exposure. Birthing parents reported on the presence of the following illnesses and conditions during pregnancy: severe nausea (i.e., beyond 6th month or accompanied by weight loss; missing n = 25, 0.31%), gestational hypertension (missing n = 28, 0.35%), persistent proteinuria (missing n = 40, 0.49%), preeclampsia or toxemia (missing n = 31, 0.38%), gestational diabetes (missing n = 28, 0.35%), severe gall bladder attack (missing n = 15, 0.19%), severe anemia (missing n = 40, 0.49%), urinary tract infection (UTI; missing n = 51, 0.63%), and any other condition requiring medical care (missing n = 15, 0.19%). Pregnancy complications included heavy bleeding requiring bed rest or treatment (missing n = 9, 0.11%), placental problems (e.g., previa, abruptio; missing n = 23, 0.28%), birthing parent accident/injury requiring medical care (missing n = 10, 0.12%), and Rh incompatibility (missing n = 138, 1.71%). The final set of questions regarding prenatal risk pertained inquired separately about substance exposure in pregnancy (yes/no) prior to and after pregnancy awareness. We created indicator variables for prescription medications, tobacco, alcohol, and illicit drugs (which included prescription medications used to get high and/or not prescribed to them; i.e., oxycontin, benzodiazepines, barbiturates, or amphetamines or methamphetamine, heroine or morphine, marijuana, cocaine or crack, cathinones, fake or synthetic marijuana, GHB, hallucinogens, inhalants, ketamine, MDMA, opioids) throughout pregnancy (i.e., collapsed across pregnancy awareness). For these outcomes, any missing information, including reports by parents that they did not remember, was assumed to mean that the exposure was not present, as we anticipated better recall for these indices. However, it should be noted that that the number of parents who reported not remembering whether substance exposure was present was 497 (6.14%) for prescription medications, 202 (2.50%) for tobacco, 230 (2.84%) for alcohol, and a range of 227 (2.80%; marijuana) to 299 (3.69%; other drugs aside from marijuana, cocaine/crack, morphine/heroin, and OxyContin) for illicit drugs. Delivery, Birth, and Developmental Milestones. Birthing parents reported on cesarean section (C-section; missing n = 8, 0.10%) delivery, child birth weight (dichotomized for low birth weight ≤ 2500 grams [ 39 ]), and whether their child had/experienced any of the following at birth: prematurity (i.e., between 28 weeks and term; missing n = 22, 0.27%), blue at birth (missing n = 80, 0.99%), did not breath at first (missing n = 68, 0.84%), required oxygen (missing n = 70, 0.87%), slow heartbeat (missing n = 81, 1.00%), jaundice that required treatment (missing n = 54, 0.67%), required a blood transfusion (missing n = 15, 0.19%), and incubation after delivery (missing n = 301, 3.72%). Finally, birthing parents rated their perceptions, on a 5-point scale, of whether motor (i.e., sitting, walking, crawling; missing n = 215, 2.67%) and speech milestones (missing n = 215, 2.67%) were met earlier, at the same time, or later than most other children. We created dichotomized variables indicating perceptions of motor and speech milestones being “somewhat later” or “much later” as a marker of broader developmental delays [ 40 ]. Outcome. Parents completed the Child Behavior Checklist (CBCL), which includes a 4-item (i.e., seems confused or in a fog; daydreams or gets lost in their thoughts; stares blankly; is underactive, slow moving, or lacks energy) CDS subscale within the DSM-oriented scales [ 41 ], which are rated on a 3-point scale. Scores on the CBCL CDS subscale correlate strongly with scores on longer, CDS-specific measures [ 42 , 43 ]. We defined elevated CDS symptoms by a T -score in the clinical range (i.e., ≥ 70); 215 (2.67%) children were categorized as having elevated CDS symptoms (Tables 1 and 2 ). Data Analytic Plan We calculated odds ratios (ORs) and 95% confidence intervals (CIs) to estimate the magnitude of bivariate associations between exposures and CDS using SPSS version 26 [ 44 ]. Given our exploratory aims, each analysis included only those participants who did not have missing information on the variables included. Results We present ORs and 95% CIs in Table 2 and Figs. 1 – 3 . Parental Risk Factors ( Fig. 1 ). All conception and early pregnancy risk indices were associated with elevated CDS symptoms in children with the exception of advanced age of either parent. We observed 60% higher odds of elevated CDS among unplanned pregnancies compared with planned pregnancies (95% CI = 1.22–2.10), and 47% higher odds among children of parents reporting pregnancy awareness after 6 weeks of gestation relative to earlier pregnancy awareness (95% CI = 1.11–1.95). Teenage parenthood was related to 93% (95% CI = 1.27–2.93) and 90% (95% CI = 1.09–3.32) higher odds compared with birthing and other parents of older ages, respectively. Prenatal Risk ( Fig. 2 ). Birthing Parent Illness in Pregnancy. Of the illnesses parents reported, persistent proteinuria was associated with highest odds of CDS symptoms, with exposed children having a 9.53-fold higher odds than unexposed children (95% CI = 4.12–22.07). Parent-reported preeclampsia/toxemia, was also related over a 2-fold higher odds of clinically elevated CDS symptoms (OR = 2.02, 95% CI = 1.29–3.17). Although parent-reported gestational hypertension was associated with 35% higher odds of CDS, this association was not statistically significant (95% CI = 0.87–2.10). Additional illnesses significantly associated with CDS with over a 2-fold higher odds included severe nausea (OR = 2.28, 95% CI = 1.67–3.12), severe anemia (OR = 2.48, 95% CI = 1.54–2.98), and UTI (OR = 2.51, 95% CI = 1.75–3.62). Associations for gestational diabetes (OR = 1.15, 95% CI = 0.69–1.94) and severe gall bladder problems (OR = 2.05, 95% CI = 0.83–5.11) were elevated but not statistically significant. Finally, we did not observe an association between other conditions requiring medical attention and CDS (OR = 1.03, 95% CI = 0.61–1.76). Pregnancy Complications. The only pregnancy complication that was significantly associated with elevated CDS symptoms in children was heavy bleeding during pregnancy with 60% higher odds of elevated CDS compared with unexposed children (95% CI = 1.54–4.40). Placental problems, birthing parent accident/injury requiring medical attention, and RH incompatibility were related to slightly higher odds of elevated CDS, but associations were not statistically significant. Prenatal Substance Exposure. Among prenatal substance exposures, birthing parent-reported illicit drug use was related to the highest odds of elevated CDS symptoms (OR = 2.89, 95% CI = 2.02–4.13). Tobacco exposure (OR = 1.90, 95% CI = 1.37–2.64) and prescription medication use (OR = 1.62, 95% CI = 1.17–2.25) were also related to significantly higher odds of clinically elevated CDS. The smallest magnitude association was observed for alcohol use in pregnancy (OR = 1.12, 95% CI = 0.83–1.52), which was not statistically significant. Delivery, Birth, and Developmental Milestones ( Fig. 3 ). Delivery and Birth. We observed the strongest associations between children being reported as blue at birth and not breathing at first, such that exposed children had roughly a 2.5-fold (OR = 2.57, 95% CI = 1.49–4.41) and 2-fold (OR = 2.10, 95% CI = 1.26–3.49) higher odds of elevated CDS than unexposed children, respectively. Although children requiring oxygen at birth was also related to a 40% higher odds of clinically elevated CDS compared to unexposed children, this association was not statistically significant. Other significant associations were observed for parent-reported jaundice needing treatment (OR = 1.88, 95% CI = 1.36–2.59) and child incubation following delivery (OR = 1.68, 95% CI = 1.13–2.51). Smaller magnitude associations that were not statistically significant included slow heartbeat at birth (OR = 1.80, 95% CI = 0.94–3.46) and children requiring blood transfusions (OR = 3.07, 95% CI = 0.72–13.07). We did not observe elevated risk of CDS related to prematurity (OR = 1.02, 95% CI = 0.65–1.60), low birth weight (OR = 0.97, 95% CI = 0.63–1.59), or C-section delivery (OR = 0.91, 95% CI = 0.68–1.23). Developmental Milestones. Children of parents reporting late motor and speech development had significantly higher odds of clinically elevated CDS symptoms, both of which were related to over a 2.5-fold higher odds of elevated CDS (motor OR = 2.61, 95% CI = 1.81–3.78; speech OR = 2.56, 95% CI = 1.91–3.43). Discussion Our study aim was to begin establishing a literature examining the prenatal, perinatal, and early life risks for CDS, a construct that co-occurs with other concerns (e.g., ADHD) with more well-established etiological roots in pregnancy and early development. We estimated bivariate associations between a wide range of early life risk factors and subsequent elevations in CDS symptoms in a large and representative sample of U.S. children using birth parent report of their child’s gestational and developmental histories and CDS symptoms at 9–10 years old. Given the dearth of current research in this area, we believe our findings substantially add to the literature and will provide a foundation for research in this area moving forward. Below, we summarize and contextualize our findings with regard for future research needs, beginning with our findings on prenatal substance exposure since this has been the primary focus of prior work. We end with a general discussion of research priorities study limitations. Expansion of Current Evidence Regarding Prenatal Substance Exposure and CDS. Our study is the second that we are aware of to document an association between tobacco exposure in pregnancy and CDS in children. Though Camprodon-Rosanas et al. [ 21 ] did not observe a significant association after adjustment for covariates, the study was likely underpowered. However, we did not adjust for covariates given the exploratory aims of the current study, which could also explain differences in findings. In fact, although prenatal tobacco exposure has been robustly associated with fetal growth restriction, prematurity, and small for gestational age [ 45 ], which maybe the mechanism by which it influences neurodevelopment [ 6 ], there is more mixed evidence regarding whether prenatal tobacco exposure causally contributes to neurodevelopmental outcomes such as ADHD [ 46 – 48 ]. Although parent-reported alcohol use in pregnancy was related to a 12% higher odds of elevated CDS symptoms compared with unexposed children, this is a comparatively small magnitude association, and the estimate was not statistically significant. Thus, our findings are most consistent with Tsang et al. [ 20 ], who found no differences in terms of CDS risk, also measured with the CBCL, though using a different cut off. In contrast, Graham et al. [ 19 ], who did observe an association, used a more comprehensive, 15-item (rather than 4 items in the CBCL) CDS measure and estimated the association using a total score rather than a binary cut off. Parent-reported illicit drug use was related to highest risk of CDS among all the prenatal substance exposures examined. Parent-reported prescription medication use was also related to higher risk for elevated CDS symptoms. However, more work is needed to specify which drugs are associated with CDS, as each drug included in the composite variables has distinct pharmacokinetic and pharmacodynamics properties. Unplanned Pregnancy, Later Pregnancy Awareness, and Teenage Parenthood May be Proxies for Prenatal Health. Our findings regarding higher risk of CDS related to unplanned pregnancies, awareness of pregnancy after 6 weeks, and teenage parenthood warrant further investigation. In addition to examination of possible confounding, such investigations should examine the extent to which these variables may be proxies for 1) a lack of prenatal care or 2) exposure to teratogens or other insults in the absence of birthing parent awareness of pregnancy or education regarding prenatal health, which may be the case for teenage pregnant people without support or resources [ 32 , 33 ]. The prevalence of unplanned pregnancies in the current study is alarmingly high (40.27%), and pregnancy awareness after 6 weeks was prevalent in approximately one fourth (24.77%) of the sample. Although in need of replication and further investigation with regard to CDS specifically, these findings in conjunction with other research [ 31 , 32 ], highlight the importance of equitable access to sex education, contraceptives, and reproductive and prenatal healthcare. Pre- and Perinatal Exposure Indices that Restrict Growth, Nutrients, and Oxygen should be Prioritized in Future Research. Among birthing parent illness, pregnancy complications, and delivery and birth indices, several patterns emerged providing convergent evidence for higher risk of CDS. First, although parent-reported gestational hypertension was modestly (though not significantly) associated with CDS, we observed the highest risk of elevated CDS symptoms pertaining to persistent proteinuria, with exposed children having almost a 10-fold higher odds of CDS compared to unexposed children. In addition, preeclampsia/toxemia was also significantly related to higher risk of elevated CDS symptoms. Given that gestational hypertension is often a precursor to preeclampsia, the latter of which is also often diagnosed when hypertension is present in combination with proteinuria, these findings provide a consistent narrative regarding the severity and progression of these illnesses in conferring risk for CDS—or alternatively—the importance of considering the confounding factors that may influence and distinguish those who progress from gestational hypertension to more severe conditions from those who do not. It is hypothesized that associations between gestational hypertensive disorders and adverse offspring outcomes may be related to decreased blood flow and oxygen to the placenta [ 49 ], which would negatively impact embryonic and fetal growth and access to nutrients and oxygen; these disorders also increase risk of and/or premature labor and delivery [ 49 ], which we discuss separately below. Parent-reported UTI and severe anemia in pregnancy were each associated with approximately 2.5 times higher odds of elevated CDS symptoms compared to children born to parents who did not report these illnesses in pregnancy. These illnesses are also the most common illnesses in pregnancy [ 50 ], making further research especially important. Both conditions can also exert effects on placental health and lead to preterm labor [ 50 – 52 ]. Additionally, one study has found iron-deficiency (a common cause of anemia) in infancy to be associated with later CDS in childhood and adolescence [ 23 ], which has implications for nutritional deprivation and possible heritable effects of anemia in relation to CDS symptoms [ 53 ]. This is also consistent with our finding over double the odds of elevated CDS symptoms related to parent-reported severe nausea and vomiting beyond 6 months of gestation or accompanied by weight loss, which may also impact fetal access to nutrients. It should be noted that if restriction of fetal growth, nutrients, and/or oxygen were important plausible mechanisms, we might have expected to observe a stronger association for placental problems. Yet, the association was small-magnitude and non-significant. Still, parent-reported heavy bleeding during pregnancy, which is commonly caused by placental problems, was related to higher risk of CDS, and may yet again identify the highest severity placental problems (e.g., significant placental rupture) and confer downstream risk. Furthermore, parent-reported jaundice that required treatment was also related to higher risk for CDS, which can also result from restricted oxygen in utero [ 54 , 55 ]. Hypoxia or lack of oxygen during labor and delivery may be another important avenue for future research as we observed over double the odds of elevated CDS symptoms related to parent reports of their child being blue and not breathing at first upon delivery compared to children whose parents did not report these exposures. We did not observe statistically significant associations for other related indices, such as slow heart beat at birth and children requiring oxygen after birth, though associations were in the same direction, just smaller in magnitude. Finally, incubation after delivery was also associated with higher risk for CDS, which may be related to many of these risk indices. Aside from those already mentioned, we observed smaller magnitude and non-significant associations for parent-reported severe gall bladder attack, gestational diabetes, Rh incompatibility, and children requiring a blood transfusion after delivery, which may suggest that these indices should be less of a research priority for future investigations of pre- and perinatal risk for elevated CDS symptoms. We also found no elevations in CDS symptoms when comparing children delivered with and without C-section delivery, premature birth, and low birth weight. We discuss prematurity and low birth weight in more detail next. Replication of Prematurity and Birth Weight Findings in a Sample that Includes Extremely Premature Children is Needed. Our study findings and their potential implications regarding investigation of fetal growth and/or premature labor and delivery are complicated by our lack of finding elevated CDS symptoms related to prematurity and low birth weight. For both of these indices, it is important to highlight that a significant limitation of the current study is the exclusion of children born extremely premature (i.e., prior to 28 weeks of gestation), thus truncating the variance of these variables to a significant degree. Indeed, this may explain why we did not replicate findings of Georgsdottir, Haraldsson [ 22 ] who observed an association between extremely low birth weight and CDS symptoms during teenage years. Furthermore, we did not have information on gestational age at birth for children that were born at and beyond term, which also limited our ability to examine indices such as small for gestational age. However, we might expect some of the observed associations in the present study to be strengthened by the inclusion of extremely premature infants, since prematurity and fetal growth restriction are one mechanism by which many of these exposures are hypothesized to take effect. Finally, the prevalence of clinically elevated CDS symptoms in the ABCD cohort is lower than in prior research using nationally representative samples, which may again support the notion that the current sample may not be capturing a subset of children at risk for CDS [ 11 , 13 ]. Late Motor and Speech Development may be Markers for CDS. We observed over a 2.5 times higher odds of elevated CDS symptoms among children whose parents perceived their children to achieve motor and speech milestones later than other children. An important next step for this and for pre- and perinatal health indices will be to rule out the explanation that these associations are only present because of the high co-occurrence between CDS and ADHD (and other neurodevelopmental outcomes). Methodological Considerations for Future Research. In addition to research on the topics discussed above, we want to highlight some important methodological next steps. First, now that we have a better understanding of which early life risk factors most strongly relate to CDS, the next step is to more rigorously examine whether observed associations might be causal. In addition to covariate adjustment, quasi-experimental designs (e.g., sibling comparisons) and methods commonly used in epidemiology (e.g., active comparators, matching) are especially important to rule out confounding by genetic and other environmental factors. Second, the use of more comprehensive measures of CDS (like those used in Graham et al. [ 19 ]) will be critical to properly detect associations, as was recently highlighted in a review identifying key directions for CDS research that also called for more etiologic and early life risk factor research [ 12 ]. Third, it will be essential to examine common and unique risk factors for CDS and commonly co-occurring difficulties, including other neurodevelopmental concerns (e.g., autism spectrum disorder). Conclusions The current study sought to estimate the magnitude of associations between a broad range of early life risk factors and elevated CDS symptoms in children at 9–10 years of age in a large and representative sample of U.S. children, in order to set a research agenda for future work on this topic. We observed initial evidence that warrants further research in many areas, including prenatal substance exposures, other pregnancy conditions and complications that may restrict fetal growth and access to nutrients and oxygen, and achievement of early life developmental milestones. Future research should prioritize examination of the likelihood that these exposure indices causally contribute to CDS. Declarations Funding: Dr. Wiggs's effort on this project was supported by the National Research Service Award in Primary Medical Care, T32HP10027, through the Health Resources and Services Administration (HRSA). Isha Lodhawala’s effort on this project was supported in part by funding from the National Institute of Mental Health (R01MH122415) (NIMH). Emma Cleary’s effort on this project was supported by funding from the National Institute on Drug Abuse (NIDA) of the National Institutes of Health Institutional Training Grant T32DA024628-14. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIMH, NIDA, or HRSA. Author Contribution K.K.W. was primarily responsible for analytic design, data preparation and cleaning, all analyses, interpretation of findings, and preparation of the manuscript (including tables and figures)T.E.C. contributed to data preparation and cleaning, preliminary analysis, and reviewed the manuscriptI.L. contributed to a literature search, preliminary analysis, and reviewed the manuscriptE.N.C. contributed to analytic design and reviewed the manuscriptK.Y. contributed to analytic design, interpretation of results, and reviewed the manuscriptS.P.B. analytic design, interpretation of results, and reviewed the manuscript Acknowledgement Data used in the preparation of this article were obtained from the Adolescent Brain Cognitive Development (ABCD) Study (https://abcdstudy.org), held in the NIMH Data Archive (NDA). This is a multisite, longitudinal study designed to recruit more than 10,000 children age 9-10 and follow them over 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, U24DA041147. A full list of supporters is available at https://abcdstudy.org/federal-partners.html. A listing of participating sites and a complete listing of the study investigators can be found at https://abcdstudy.org/consortium_members/. ABCD consortium investigators designed and implemented the study and/or provided data but did not necessarily participate in the analysis or writing of this report. This manuscript reflects the views of the authors and may not reflect the opinions or views of the NIH or ABCD consortium investigators. The ABCD data repository grows and changes over time. The ABCD data used in this report came from [10.15154/bkya-7b87]. Data Availability The DOI for this study through the national data archive can be found at https://nda.nih.gov/general-query.html under the following assignment: DOI: 10.15154/z563-zd24 References Barker DJP (1998) Mothers, babies and disease in later life. No Title) Barker D, Osmond C (1988) Low birth weight and hypertension. BMJ: Br Med J 297(6641):134 Barker DJ (1990) The fetal and infant origins of adult disease. BMJ: Br Med J 301(6761):1111 Bale TL et al (2010) Early life programming and neurodevelopmental disorders. Biol Psychiatry 68(4):314–319 Nigg JT et al (2020) Development of ADHD: Etiology, heterogeneity, and early life course. Annual Rev Dev Psychol 2:559–583 Kim JH et al (2020) Environmental risk factors, protective factors, and peripheral biomarkers for ADHD: an umbrella review. 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J Atten Disord 21(8):632–641 Georgsdottir I, Haraldsson A, Dagbjartsson A (2013) Behavior and well-being of extremely low birth weight teenagers in Iceland. Early Hum Dev 89(12):999–1003 East PL et al (2023) Iron deficiency in infancy and sluggish cognitive tempo and ADHD symptoms in childhood and adolescence. J Clin Child Adolesc Psychol 52(2):259–270 Heeringa SG, Berglund PA (2020) A guide for population-based analysis of the Adolescent Brain Cognitive Development (ABCD) Study baseline data. BioRxiv, : p. 2020.02. 10.942011 Garavan H et al (2018) Recruiting the ABCD sample: Design considerations and procedures. Dev Cogn Neurosci 32:16–22 Paul SE et al (2021) Associations between prenatal cannabis exposure and childhood outcomes: results from the ABCD study. JAMA psychiatry 78(1):64–76 Moreau AL et al (2023) Prenatal selective serotonin reuptake inhibitor exposure, depression, and brain morphology in middle childhood: results from the ABCD study. 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Matern Child Health J 21:715–726 Baker BH et al (2023) Maternal age at birth and child attention-deficit hyperactivity disorder: causal association or familial confounding? J Child Psychol Psychiatry 64(2):299–310 Du J et al (2022) Association between parental age, brain structure, and behavioral and cognitive problems in children. Mol Psychiatry 27(2):967–975 Lean SC et al (2017) Advanced maternal age and adverse pregnancy outcomes: A systematic review and meta-analysis. PLoS ONE 12(10):e0186287 Zhang C, Yan L, Qiao J (2022) Effect of advanced parental age on pregnancy outcome and offspring health. J Assist Reprod Genet 39(9):1969–1986 Min X, Li C, Yan Y (2021) Parental age and the risk of ADHD in offspring: a systematic review and meta-analysis. Int J Environ Res Public Health 18(9):4939 Momany AM, Kamradt JM, Nikolas MA (2018) A meta-analysis of the association between birth weight and attention deficit hyperactivity disorder. J Abnorm Child Psychol 46:1409–1426 Zhuo H et al (2022) Developmental Milestones of Infancy and Associations with Later Childhood Neurodevelopmental Outcomes in the Adolescent Brain Cognitive Development (ABCD) Study. Children 9(10):1424 Manual for the ASEBA preschool forms and profiles . Vol. 30. 2000: Burlington, VT: University of Vermont, Research center for children,youth &#8230 Skirbekk B et al (2011) The relationship between sluggish cognitive tempo, subtypes of attention-deficit/hyperactivity disorder, and anxiety disorders. J Abnorm Child Psychol 39(4):513–525 Burns GL, Becker SP (2022) Convergent and discriminant validity of the Child and Adolescent Behavior Inventory Scale scores with well-established psychopathology and academic achievement measures in adolescents with ADHD. Assessment 29(5):1086–1098 IBM Corp Released 2019. IBM SPSS Statistics for Windows, Version 26.0. Armonk, NY: IBM Corp Moore KL, Persaud TVN, Torchia MG (2018) The Developing Human-E-Book: The Developing Human-E-Book. Elsevier Health Sciences D'Onofrio BM et al (2008) Smoking during pregnancy and offspring externalizing problems: an exploration of genetic and environmental confounds. Dev Psychopathol 20(1):139–164 Skoglund C et al (2014) Familial confounding of the association between maternal smoking during pregnancy and ADHD in offspring. J Child Psychol Psychiatry 55(1):61–68 Knopik VS et al (2016) Smoking during pregnancy and ADHD risk: A genetically informed, multiple-rater approach. Am J Med Genet Part B: Neuropsychiatric Genet 171(7):971–981 Maher GM et al (2018) Association of hypertensive disorders of pregnancy with risk of neurodevelopmental disorders in offspring: a systematic review and meta-analysis. JAMA psychiatry 75(8):809–819 Szweda H, Jóźwik M (2016) Urinary tract infections during pregnancy-an updated overview. Dev Period Med 20(4):263–272 Lelic M et al (2014) Influence of maternal anemia during pregnancy on placenta and newborns. Med Archives 68(3):184 Roberts H, Bourque SL, Renaud SJ (2020) Maternal iron homeostasis: effect on placental development and function. Reproduction 160(4):R65–R78 Barrera-Reyes PK, Tejero ME (2019) Genetic variation influencing hemoglobin levels and risk for anemia across populations, vol 1450. Annals of the New York Academy of Sciences, pp 32–46. 1 Dani C et al (2018) Changes in bilirubin in infants with hypoxic–ischemic encephalopathy. Eur J Pediatrics 177:1795–1801 Mitra S, Rennie J (2017) Neonatal jaundice: aetiology, diagnosis and treatment. Br J Hosp Med 78(12):699–704 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 10 Mar, 2025 Read the published version in European Child & Adolescent Psychiatry → Version 1 posted Editorial decision: Revision requested 09 Nov, 2024 Reviews received at journal 09 Nov, 2024 Reviews received at journal 23 Jul, 2024 Reviewers agreed at journal 15 Jul, 2024 Reviewers agreed at journal 15 Jul, 2024 Reviewers invited by journal 24 May, 2024 Submission checks completed at journal 23 May, 2024 Editor assigned by journal 23 May, 2024 First submitted to journal 23 May, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {\"props\":{\"pageProps\":{\"initialData\":{\"identity\":\"rs-4468007\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":false,\"archivedVersions\":[],\"articleType\":\"Research Article\",\"associatedPublications\":[],\"authors\":[{\"id\":309683184,\"identity\":\"48a3564a-eeb2-45bd-925b-13dcb6d93af5\",\"order_by\":0,\"name\":\"Kelsey K. Wiggs\",\"email\":\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+ElEQVRIiWNgGAWjYBACCQbmBjCDDUR8YGBIIEILI0IL4wyStIAAMw8xWiTbG5s/fGxjSOzjX375s02NXZ5u+wHGxxW/cGuR5jnYJjkTqKVN4k2ZdM6x5GKzMwnMhmf7cGuRk0hsY+ZtY8htkziTxpzbcCBx2w0GNsnGHjxa5B82f/4L0ZL82ZIYLdISjA3SjCAt/O0HpBlhWhp+4PF+T2KbZM85ifo2CR42yZ5jyYnbziQ2GzY24NYicfzw4Q8/ymyM5fuPP/7wo8YucdvxwwcfNvzBrQUMGNkkgJpzDGDcBgagUwkAkJn8xx+giYyCUTAKRsEogAAAnm9X5kPSXggAAAAASUVORK5CYII=\",\"orcid\":\"\",\"institution\":\"Cincinnati Children’s Hospital Medical Center\",\"correspondingAuthor\":true,\"prefix\":\"\",\"firstName\":\"Kelsey\",\"middleName\":\"K.\",\"lastName\":\"Wiggs\",\"suffix\":\"\"},{\"id\":309683185,\"identity\":\"7c592d86-65cf-418b-9488-6a1213a27a72\",\"order_by\":1,\"name\":\"Taryn E. 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Although researchers are still pursuing which pre- and perinatal risk factors cause outcomes [\\u003cspan citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e5\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR6\\\" class=\\\"CitationRef\\\"\\u003e6\\u003c/span\\u003e], certain genetic and environmental risk factors are likely to predispose the developing brain to neurodivergence (e.g., ADHD, autism spectrum disorders [ASD]) generally [\\u003cspan additionalcitationids=\\\"CR8 CR9\\\" citationid=\\\"CR7\\\" class=\\\"CitationRef\\\"\\u003e7\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR10\\\" class=\\\"CitationRef\\\"\\u003e10\\u003c/span\\u003e], while others may specify ultimate developmental outcomes [\\u003cspan citationid=\\\"CR7\\\" class=\\\"CitationRef\\\"\\u003e7\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR10\\\" class=\\\"CitationRef\\\"\\u003e10\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eCognitive disengagement syndrome (CDS; previously called sluggish cognitive tempo [SCT]) co-occurs in up to 40% of children with ADHD [\\u003cspan additionalcitationids=\\\"CR12 CR13\\\" citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR14\\\" class=\\\"CitationRef\\\"\\u003e14\\u003c/span\\u003e]. This may suggest etiologic overlap, yet very little is known about the early life origins of CDS [\\u003cspan citationid=\\\"CR12\\\" class=\\\"CitationRef\\\"\\u003e12\\u003c/span\\u003e]. First studied in the 1980s, CDS is characterized by internally-focused distraction (e.g., excessive daydreaming, zoning out), mental confusion, and hypo-activity (e.g., lethargy, drowsiness) [\\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e15\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR16\\\" class=\\\"CitationRef\\\"\\u003e16\\u003c/span\\u003e] .In early factor analytic studies, CDS emerged as a third dimension of ADHD alongside inattentive and hyperactive-impulsive dimensions [\\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e15\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR16\\\" class=\\\"CitationRef\\\"\\u003e16\\u003c/span\\u003e], though it is still debated whether CDS should be considered a presentation of ADHD, its own disorder, or a transdiagnostic phenotypic trait [\\u003cspan citationid=\\\"CR12\\\" class=\\\"CitationRef\\\"\\u003e12\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e17\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR18\\\" class=\\\"CitationRef\\\"\\u003e18\\u003c/span\\u003e]. Furthermore, CDS is related to difficulties (e.g., academic, social, and mental health) beyond what is accounted for by ADHD symptoms alone [\\u003cspan citationid=\\\"CR12\\\" class=\\\"CitationRef\\\"\\u003e12\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eOnly three studies have examined prenatal risk for CDS [\\u003cspan additionalcitationids=\\\"CR20\\\" citationid=\\\"CR19\\\" class=\\\"CitationRef\\\"\\u003e19\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR21\\\" class=\\\"CitationRef\\\"\\u003e21\\u003c/span\\u003e]. Two studies have examined the association between prenatal alcohol exposure and CDS, finding opposing results [\\u003cspan citationid=\\\"CR19\\\" class=\\\"CitationRef\\\"\\u003e19\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR20\\\" class=\\\"CitationRef\\\"\\u003e20\\u003c/span\\u003e]. Graham et al. [\\u003cspan citationid=\\\"CR19\\\" class=\\\"CitationRef\\\"\\u003e19\\u003c/span\\u003e] found higher mean scores measured by a 15-item CDS scale among children 8\\u0026ndash;16 exposed prenatally to heavy alcohol use [\\u003cspan citationid=\\\"CR19\\\" class=\\\"CitationRef\\\"\\u003e19\\u003c/span\\u003e]. However, in a more recent study comparing children ages 7.5\\u0026ndash;9.5 with and without fetal alcohol spectrum disorders, there were no differences between groups regarding the odds of having a CDS score in the \\u0026ldquo;borderline\\u0026rdquo; or \\u0026ldquo;clinical\\u0026rdquo; range (i.e., \\u003cem\\u003eT\\u003c/em\\u003e-score\\u0026thinsp;\\u0026ge;\\u0026thinsp;65) on the Child Behavior Checklist (CBCL) or Teacher\\u0026rsquo;s Report Form (TRF) [\\u003cspan citationid=\\\"CR20\\\" class=\\\"CitationRef\\\"\\u003e20\\u003c/span\\u003e]. There are many possible reasons for these discrepant findings, including that only 12 children had elevated CDS symptoms in the more recent study [\\u003cspan citationid=\\\"CR20\\\" class=\\\"CitationRef\\\"\\u003e20\\u003c/span\\u003e], which limits statistical power. Finally, Comprodon-Rosanas et al. [\\u003cspan citationid=\\\"CR21\\\" class=\\\"CitationRef\\\"\\u003e21\\u003c/span\\u003e] observed an association between prenatal tobacco exposure and \\u0026ldquo;borderline\\u0026rdquo; or \\u0026ldquo;clinically\\u0026rdquo; elevated CDS scores measured by the CBCL among children ages 7\\u0026ndash;10, though the association was no longer significant after adjustment for covariates; it should again be noted that only 20 children were observed to have elevated CDS symptoms [\\u003cspan citationid=\\\"CR21\\\" class=\\\"CitationRef\\\"\\u003e21\\u003c/span\\u003e]. In addition to these prenatal studies, there has been one study each documenting an association between extremely low birth weight [\\u003cspan citationid=\\\"CR22\\\" class=\\\"CitationRef\\\"\\u003e22\\u003c/span\\u003e] and iron deficiency [\\u003cspan citationid=\\\"CR23\\\" class=\\\"CitationRef\\\"\\u003e23\\u003c/span\\u003e] in infants with subsequent CDS symptoms in youth.\\u003c/p\\u003e \\u003cp\\u003eIdentification of early life risk factors for CDS is important because findings regarding common (e.g., to CDS and ADHD) and unique etiologic risk factors may 1) shape ongoing debate and decisions regarding whether CDS is best conceptualized as a distinct phenomenon or as a presentation of ADHD [\\u003cspan citationid=\\\"CR12\\\" class=\\\"CitationRef\\\"\\u003e12\\u003c/span\\u003e], 2) influence prevention and intervention efforts, and 3) guide theory regarding CDS more broadly. The aim of this study was to examine the magnitude of bivariate associations, in a far larger sample than prior literature, to illuminate which risk factors may be most important to prioritize in future investigations.\\u003c/p\\u003e\"},{\"header\":\"Methods\",\"content\":\"\\u003cdiv id=\\\"Sec3\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eData Source\\u003c/h2\\u003e \\u003cp\\u003e We conducted a secondary analysis of baseline data from the Adolescent Brain Cognitive Development (ABCD) study, which was considered exempt from Institutional Review Board approval. The ABCD study is a prospective, representative twenty-two site study of U.S. children [\\u003cspan citationid=\\\"CR24\\\" class=\\\"CitationRef\\\"\\u003e24\\u003c/span\\u003e]. Baseline data were collected from 2017 to 2018, when children were roughly 9\\u0026ndash;10 years old. We used data from Release 4.0 in the current study (\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e10.15154/bkya-7b87\\u003c/span\\u003e\\u003cspan address=\\\"10.15154/bkya-7b87\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e). Participant recruitment procedures are described elsewhere [\\u003cspan citationid=\\\"CR25\\\" class=\\\"CitationRef\\\"\\u003e25\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cdiv id=\\\"Sec4\\\" class=\\\"Section3\\\"\\u003e \\u003ch2\\u003eSample\\u003c/h2\\u003e \\u003cp\\u003eThe ABCD study (N\\u0026thinsp;=\\u0026thinsp;11,878) did not include children that were born extremely premature (i.e., born at less than 28 weeks of gestation). For our study, we excluded children who did not have a Developmental History Questionnaire (exposures) completed by their biological mother/birthing parent (n\\u0026thinsp;=\\u0026thinsp;1,797), as\\u0026mdash;like other researchers who have used these data\\u0026mdash;we anticipated particular difficulty in recall for other caregivers [\\u003cspan citationid=\\\"CR26\\\" class=\\\"CitationRef\\\"\\u003e26\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR27\\\" class=\\\"CitationRef\\\"\\u003e27\\u003c/span\\u003e]. Next, we excluded children without valid reported birth weight (n\\u0026thinsp;=\\u0026thinsp;3), multiples (n\\u0026thinsp;=\\u0026thinsp;1,976) [\\u003cspan citationid=\\\"CR28\\\" class=\\\"CitationRef\\\"\\u003e28\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR29\\\" class=\\\"CitationRef\\\"\\u003e29\\u003c/span\\u003e], and children with missing multiples status (n\\u0026thinsp;=\\u0026thinsp;4) [\\u003cspan additionalcitationids=\\\"CR29 CR30\\\" citationid=\\\"CR28\\\" class=\\\"CitationRef\\\"\\u003e28\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR31\\\" class=\\\"CitationRef\\\"\\u003e31\\u003c/span\\u003e]. Finally, we excluded two children without information on the outcome (see Measures), resulting in a final sample of 8,096 children. We present information on age, sex, and race/ethnicity in Table\\u0026nbsp;\\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e. Of note, from here onward we use the terms birthing parent and other parent to refer to female and male parents, respectively, as we did not have information on gender identity.\\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab1\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 1\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003eChild Demographics Stratified by CDS Group\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"3\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eNo CDS Elevation\\u003c/p\\u003e \\u003cp\\u003e(\\u003cem\\u003eT\\u003c/em\\u003e-score\\u0026thinsp;\\u0026gt;\\u0026thinsp;70; n\\u0026thinsp;=\\u0026thinsp;7881)\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eCDS Elevation\\u003c/p\\u003e \\u003cp\\u003e(\\u003cem\\u003eT\\u003c/em\\u003e-Score\\u0026thinsp;\\u003cspan type=\\\"Underline\\\" class=\\\"Underline\\\" name=\\\"Emphasis\\\"\\u003e\\u0026ge;\\u003c/span\\u003e\\u0026thinsp;70; n\\u0026thinsp;=\\u0026thinsp;215)\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eMean (SD)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eMean (SD)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eAge at Research Visit\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e118.51 (7.57) months\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e118.40 (7.70) months\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003en (%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003en (%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eSex Assigned at Birth\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eFemale\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e3786 (48.04)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e83 (38.60)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eMale\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e4095 (51.96)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e132 (61.39)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eRace\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eAsian\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e481 (6.10)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e12 (5.58)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eBlack\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1673 (21.23)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e67 (31.16)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eNative/Indigenous Alaskan or American\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e266 (3.38)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e11 (5.12)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eNative Hawaiian or Pacific Islander\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e44 (0.56)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e4 (1.86)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eWhite\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e5811 (73.73)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e144 (66.98)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eOther\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e574 (7.28)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e25 (11.63)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eUnknown\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e119 (1.51)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e1 (0.47)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eHispanic/Latin\\u0026eacute;\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e22 (0.28)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e1 (0.47)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003c/table\\u003e\\u003c/div\\u003e\\u003cp\\u003e \\u003cp\\u003eNote CDS\\u0026thinsp;=\\u0026thinsp;cognitive disengagement syndrome (termed \\u0026lsquo;sluggish cognitive tempo\\u0026rsquo; on the Child Behavior Checklist scale used to define the construct in this study).\\u003c/p\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec5\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eMeasures\\u003c/h2\\u003e \\u003cp\\u003e \\u003cb\\u003eExposures.\\u003c/b\\u003e We only excluded variables that we believed would be especially susceptible to recall difficulties (e.g., exact ages in months when developmental milestones occurred, dose/frequency of medication and drug use), outside the scope of the current study (e.g., vitamin use), and that were deemed too rare in frequency (i.e., rubella and convulsions in pregnancy). We present the frequencies and percentages of children exposed among the total sample and the elevated CDS group in Table\\u0026nbsp;\\u003cspan refid=\\\"Tab2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e. We report on frequency of missing for each variable below.\\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab2\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 2\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003eExposure Frequencies Among Total Sample, Elevated CDS Sample, and Odds Ratios Estimating Associations between Exposures and CDS\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"4\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eTotal Sample (N\\u0026thinsp;=\\u0026thinsp;8,096)\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c4\\\" namest=\\\"c3\\\"\\u003e \\u003cp\\u003eCDS Elevation (\\u003cem\\u003eT\\u003c/em\\u003e-Score\\u0026thinsp;\\u003cspan type=\\\"Underline\\\" class=\\\"Underline\\\" name=\\\"Emphasis\\\"\\u003e\\u0026ge;\\u003c/span\\u003e\\u0026thinsp;70; n\\u0026thinsp;=\\u0026thinsp;215)\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003en (%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003en (%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eOdds Ratio (95% CI)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eParental Risk Factors\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eUnplanned Pregnancy\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e3,260 (40.27)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e111 (51.63)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1.60 (1.22\\u0026ndash;2.10)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePregnancy Awareness after 6\\u003c/p\\u003e \\u003cp\\u003eWeeks\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e2,248 (24.77)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e77 (35.81)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1.47 (1.11\\u0026ndash;1.95)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eTeen Birthing Parent\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e549 (6.78)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e26 (12.09)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1.93 (1.27\\u0026ndash;2.93)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eBirthing Parent Age of 40+\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e348 (4.30)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e7 (3.26)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.74 (0.35\\u0026ndash;1.59)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eTeen Other Parent\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e292 (3.61)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e14 (6.51)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1.90 (1.09\\u0026ndash;3.32)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eOther Parent Age of 45+\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e290 (3.58)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e8 (3.72)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1.04 (0.51\\u0026ndash;2.13)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eBirthing Parent Illness in Pregnancy\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eSevere Nausea\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1,125 (13.90)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e56 (26.05)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e2.28 (1.67\\u0026ndash;3.12)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eGestational Hypertension\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e678 (8.38)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e23 (10.70)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1.35 (0.87\\u0026ndash;2.10)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePersistent Proteinuria\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e35 (0.43)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e7 (3.26)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e9.53 (4.12\\u0026ndash;22.07)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePreeclampsia/Toxemia\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e448 (5.53)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e22 (10.23)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e2.02 (1.29\\u0026ndash;3.17)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eGestational Diabetes\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e535 (6.61)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e16 (7.44)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1.15 (0.69\\u0026ndash;1.94)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eSevere Gall Bladder Attack\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e96 (1.19)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e5 (2.33)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e2.05 (0.83\\u0026ndash;5.11)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eSevere Anemia\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e338 (4.18)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e20 (9.30)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e2.48 (1.54\\u0026ndash;2.98)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eUrinary Tract Infection\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e645 (7.97)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e37 (17.21)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e2.51 (1.75\\u0026ndash;3.62)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eAny other condition requiring\\u003c/p\\u003e \\u003cp\\u003emedical care\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e552 (6.82)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e15 (6.98)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1.03 (0.61\\u0026ndash;1.76)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePregnancy Complications\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eHeavy Bleeding\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e253 (3.13)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e16 (7.44)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e2.60 (1.54\\u0026ndash;4.40)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePlacental Problems\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e209 (2.58)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e6 (2.79)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1.10 (0.48\\u0026ndash;2.50)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eBirth Parent Accident/Injury\\u003c/p\\u003e \\u003cp\\u003eRequiring Medical Care\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e151 (1.87)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e5 (2.33)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1.27 (0.51\\u0026ndash;2.13)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eRH Incompatibility\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e230 (2.84)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e7 (3.26)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1.18 (0.55\\u0026ndash;2.53)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePrenatal Substance Exposure\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePrescription Medication\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1,236 (15.27)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e48 (22.33)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1.62 (1.17\\u0026ndash;2.25)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eTobacco\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1,082 (13.37)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e48 (22.33)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1.90 (1.37\\u0026ndash;2.64)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eAlcohol\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e2,043 (25.23)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e59 (27.44)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1.12 (0.83\\u0026ndash;1.52)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eIllicit Drugs\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e601 (7.42)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e39 (18.14)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e2.89 (2.02\\u0026ndash;4.13)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eDelivery and Birth\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePrematurity\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e818 (10.10)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e22 (10.23)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1.02 (0.65\\u0026ndash;1.60)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eLow Birth Weight\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e755 (9.33)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e20 (9.30)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.97 (0.63\\u0026ndash;1.59)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eC-section\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e2,488 (30.73)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e62 (28.84)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.91 (0.68\\u0026ndash;1.23)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eBlue at Birth\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e241 (2.98)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e15 (6.98)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e2.57 (1.49\\u0026ndash;4.41)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eDid not Breath at First\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e335 (4.14)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e17 (7.90)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e2.10 (1.26\\u0026ndash;3.49)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eRequired Oxygen\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e475 (5.87)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e17 (7.90)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1.40 (0.85\\u0026ndash;2.32)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eSlow Heartbeat\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e218 (2.69)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e10 (4.65)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1.80 (0.94\\u0026ndash;3.46)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eJaundice Requiring Treatment\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1,192 (14.72)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e51 (23.72)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1.88 (1.36\\u0026ndash;2.59)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eRequired Blood Transfusion\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e26 (0.32)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e2 (0.93)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e3.07 (0.72\\u0026ndash;13.07)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eIncubated after Delivery\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e725 (8.96)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e29 (13.49)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1.68 (1.13\\u0026ndash;2.51)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eDevelopmental Milestones\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eLate Motor Development\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e599 (7.40)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e36 (16.74)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e2.61 (1.81\\u0026ndash;3.78)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eLate Speech Development\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1,276 (15.76)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e68 (31.63)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e2.56 (1.91\\u0026ndash;3.43)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003cp\\u003e Note CDS\\u0026thinsp;=\\u0026thinsp;cognitive disengagement syndrome.\\u003c/p\\u003e\\u003c/p\\u003e \\u003cp\\u003e\\u003cem\\u003eParental Risk Factors.\\u003c/em\\u003e Birthing parents reported on whether their pregnancy was planned (missing n\\u0026thinsp;=\\u0026thinsp;47, 0.58%), when they became aware they were pregnant (missing n\\u0026thinsp;=\\u0026thinsp;514, 6.35%), their age and the age of the other biological parent when their child was born (missing n\\u0026thinsp;=\\u0026thinsp;66, 0.82%; missing n\\u0026thinsp;=\\u0026thinsp;281, 3.47%; respectively). Because unplanned pregnancies may confer risk to embryonic and fetal development (e.g., via lack of prenatal care in absence of pregnancy awareness) [\\u003cspan citationid=\\\"CR32\\\" class=\\\"CitationRef\\\"\\u003e32\\u003c/span\\u003e] and serve as an indication of broader environmental risk [\\u003cspan citationid=\\\"CR32\\\" class=\\\"CitationRef\\\"\\u003e32\\u003c/span\\u003e], we created an indicator variable for unplanned pregnancy. We also created an indicator variable for pregnancy awareness after 6 weeks of gestation, which is after the observed median in our data (5 weeks) and also after the mean (5.5 weeks) observed in other research [\\u003cspan citationid=\\\"CR33\\\" class=\\\"CitationRef\\\"\\u003e33\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR34\\\" class=\\\"CitationRef\\\"\\u003e34\\u003c/span\\u003e]. Finally, we dichotomized parental age variables in two ways based on prior literature demonstrating a parabolic pattern of risk for adverse outcomes in children [\\u003cspan additionalcitationids=\\\"CR35 CR36\\\" citationid=\\\"CR34\\\" class=\\\"CitationRef\\\"\\u003e34\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR37\\\" class=\\\"CitationRef\\\"\\u003e37\\u003c/span\\u003e], including risk for ADHD [\\u003cspan citationid=\\\"CR38\\\" class=\\\"CitationRef\\\"\\u003e38\\u003c/span\\u003e]: teenage (i.e., under 20) and advanced age (i.e., 40\\u0026thinsp;+\\u0026thinsp;years for birthing parents and 45\\u0026thinsp;+\\u0026thinsp;years for other biological parent).\\u003c/p\\u003e \\u003cp\\u003e \\u003cem\\u003ePrenatal Risk: Birthing Parent Illness, Pregnancy Complications, and Substance Exposure.\\u003c/em\\u003e Birthing parents reported on the presence of the following illnesses and conditions during pregnancy: severe nausea (i.e., beyond 6th month or accompanied by weight loss; missing n\\u0026thinsp;=\\u0026thinsp;25, 0.31%), gestational hypertension (missing n\\u0026thinsp;=\\u0026thinsp;28, 0.35%), persistent proteinuria (missing n\\u0026thinsp;=\\u0026thinsp;40, 0.49%), preeclampsia or toxemia (missing n\\u0026thinsp;=\\u0026thinsp;31, 0.38%), gestational diabetes (missing n\\u0026thinsp;=\\u0026thinsp;28, 0.35%), severe gall bladder attack (missing n\\u0026thinsp;=\\u0026thinsp;15, 0.19%), severe anemia (missing n\\u0026thinsp;=\\u0026thinsp;40, 0.49%), urinary tract infection (UTI; missing n\\u0026thinsp;=\\u0026thinsp;51, 0.63%), and any other condition requiring medical care (missing n\\u0026thinsp;=\\u0026thinsp;15, 0.19%). Pregnancy complications included heavy bleeding requiring bed rest or treatment (missing n\\u0026thinsp;=\\u0026thinsp;9, 0.11%), placental problems (e.g., previa, abruptio; missing n\\u0026thinsp;=\\u0026thinsp;23, 0.28%), birthing parent accident/injury requiring medical care (missing n\\u0026thinsp;=\\u0026thinsp;10, 0.12%), and Rh incompatibility (missing n\\u0026thinsp;=\\u0026thinsp;138, 1.71%).\\u003c/p\\u003e \\u003cp\\u003eThe final set of questions regarding prenatal risk pertained inquired separately about substance exposure in pregnancy (yes/no) prior to and after pregnancy awareness. We created indicator variables for prescription medications, tobacco, alcohol, and illicit drugs (which included prescription medications used to get high and/or not prescribed to them; i.e., oxycontin, benzodiazepines, barbiturates, or amphetamines or methamphetamine, heroine or morphine, marijuana, cocaine or crack, cathinones, fake or synthetic marijuana, GHB, hallucinogens, inhalants, ketamine, MDMA, opioids) throughout pregnancy (i.e., collapsed across pregnancy awareness). For these outcomes, any missing information, including reports by parents that they did not remember, was assumed to mean that the exposure was not present, as we anticipated better recall for these indices. However, it should be noted that that the number of parents who reported not remembering whether substance exposure was present was 497 (6.14%) for prescription medications, 202 (2.50%) for tobacco, 230 (2.84%) for alcohol, and a range of 227 (2.80%; marijuana) to 299 (3.69%; other drugs aside from marijuana, cocaine/crack, morphine/heroin, and OxyContin) for illicit drugs.\\u003c/p\\u003e \\u003cp\\u003e \\u003cem\\u003eDelivery, Birth, and Developmental Milestones.\\u003c/em\\u003e Birthing parents reported on cesarean section (C-section; missing n\\u0026thinsp;=\\u0026thinsp;8, 0.10%) delivery, child birth weight (dichotomized for low birth weight\\u0026thinsp;\\u003cspan type=\\\"Underline\\\" class=\\\"Underline\\\" name=\\\"Emphasis\\\"\\u003e\\u0026le;\\u003c/span\\u003e\\u0026thinsp;2500 grams [\\u003cspan citationid=\\\"CR39\\\" class=\\\"CitationRef\\\"\\u003e39\\u003c/span\\u003e]), and whether their child had/experienced any of the following at birth: prematurity (i.e., between 28 weeks and term; missing n\\u0026thinsp;=\\u0026thinsp;22, 0.27%), blue at birth (missing n\\u0026thinsp;=\\u0026thinsp;80, 0.99%), did not breath at first (missing n\\u0026thinsp;=\\u0026thinsp;68, 0.84%), required oxygen (missing n\\u0026thinsp;=\\u0026thinsp;70, 0.87%), slow heartbeat (missing n\\u0026thinsp;=\\u0026thinsp;81, 1.00%), jaundice that required treatment (missing n\\u0026thinsp;=\\u0026thinsp;54, 0.67%), required a blood transfusion (missing n\\u0026thinsp;=\\u0026thinsp;15, 0.19%), and incubation after delivery (missing n\\u0026thinsp;=\\u0026thinsp;301, 3.72%). Finally, birthing parents rated their perceptions, on a 5-point scale, of whether motor (i.e., sitting, walking, crawling; missing n\\u0026thinsp;=\\u0026thinsp;215, 2.67%) and speech milestones (missing n\\u0026thinsp;=\\u0026thinsp;215, 2.67%) were met earlier, at the same time, or later than most other children. We created dichotomized variables indicating perceptions of motor and speech milestones being \\u0026ldquo;somewhat later\\u0026rdquo; or \\u0026ldquo;much later\\u0026rdquo; as a marker of broader developmental delays [\\u003cspan citationid=\\\"CR40\\\" class=\\\"CitationRef\\\"\\u003e40\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003e \\u003cb\\u003eOutcome.\\u003c/b\\u003e Parents completed the Child Behavior Checklist (CBCL), which includes a 4-item (i.e., seems confused or in a fog; daydreams or gets lost in their thoughts; stares blankly; is underactive, slow moving, or lacks energy) CDS subscale within the DSM-oriented scales [\\u003cspan citationid=\\\"CR41\\\" class=\\\"CitationRef\\\"\\u003e41\\u003c/span\\u003e], which are rated on a 3-point scale. Scores on the CBCL CDS subscale correlate strongly with scores on longer, CDS-specific measures [\\u003cspan citationid=\\\"CR42\\\" class=\\\"CitationRef\\\"\\u003e42\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR43\\\" class=\\\"CitationRef\\\"\\u003e43\\u003c/span\\u003e]. We defined elevated CDS symptoms by a \\u003cem\\u003eT\\u003c/em\\u003e-score in the clinical range (i.e., \\u003cspan type=\\\"Underline\\\" class=\\\"Underline\\\" name=\\\"Emphasis\\\"\\u003e\\u0026ge;\\u003c/span\\u003e\\u0026thinsp;70); 215 (2.67%) children were categorized as having elevated CDS symptoms (Tables\\u0026nbsp;\\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e and \\u003cspan refid=\\\"Tab2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e).\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec6\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eData Analytic Plan\\u003c/h2\\u003e \\u003cp\\u003eWe calculated odds ratios (ORs) and 95% confidence intervals (CIs) to estimate the magnitude of bivariate associations between exposures and CDS using SPSS version 26 [\\u003cspan citationid=\\\"CR44\\\" class=\\\"CitationRef\\\"\\u003e44\\u003c/span\\u003e]. Given our exploratory aims, each analysis included only those participants who did not have missing information on the variables included.\\u003c/p\\u003e \\u003c/div\\u003e\"},{\"header\":\"Results\",\"content\":\"\\u003cp\\u003eWe present ORs and 95% CIs in Table\\u0026nbsp;\\u003cspan refid=\\\"Tab2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e and Figs.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e\\u0026ndash;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e.\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\u003e \\u003cb\\u003eParental Risk Factors (\\u003c/b\\u003eFig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e\\u003cb\\u003e).\\u003c/b\\u003e All conception and early pregnancy risk indices were associated with elevated CDS symptoms in children with the exception of advanced age of either parent. We observed 60% higher odds of elevated CDS among unplanned pregnancies compared with planned pregnancies (95% CI\\u0026thinsp;=\\u0026thinsp;1.22\\u0026ndash;2.10), and 47% higher odds among children of parents reporting pregnancy awareness after 6 weeks of gestation relative to earlier pregnancy awareness (95% CI\\u0026thinsp;=\\u0026thinsp;1.11\\u0026ndash;1.95). Teenage parenthood was related to 93% (95% CI\\u0026thinsp;=\\u0026thinsp;1.27\\u0026ndash;2.93) and 90% (95% CI\\u0026thinsp;=\\u0026thinsp;1.09\\u0026ndash;3.32) higher odds compared with birthing and other parents of older ages, respectively.\\u003c/p\\u003e \\u003cp\\u003e \\u003cb\\u003ePrenatal Risk (\\u003c/b\\u003eFig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e\\u003cb\\u003e).\\u003c/b\\u003e\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\u003e \\u003cem\\u003eBirthing Parent Illness in Pregnancy.\\u003c/em\\u003e Of the illnesses parents reported, persistent proteinuria was associated with highest odds of CDS symptoms, with exposed children having a 9.53-fold higher odds than unexposed children (95% CI\\u0026thinsp;=\\u0026thinsp;4.12\\u0026ndash;22.07). Parent-reported preeclampsia/toxemia, was also related over a 2-fold higher odds of clinically elevated CDS symptoms (OR\\u0026thinsp;=\\u0026thinsp;2.02, 95% CI\\u0026thinsp;=\\u0026thinsp;1.29\\u0026ndash;3.17). Although parent-reported gestational hypertension was associated with 35% higher odds of CDS, this association was not statistically significant (95% CI\\u0026thinsp;=\\u0026thinsp;0.87\\u0026ndash;2.10). Additional illnesses significantly associated with CDS with over a 2-fold higher odds included severe nausea (OR\\u0026thinsp;=\\u0026thinsp;2.28, 95% CI\\u0026thinsp;=\\u0026thinsp;1.67\\u0026ndash;3.12), severe anemia (OR\\u0026thinsp;=\\u0026thinsp;2.48, 95% CI\\u0026thinsp;=\\u0026thinsp;1.54\\u0026ndash;2.98), and UTI (OR\\u0026thinsp;=\\u0026thinsp;2.51, 95% CI\\u0026thinsp;=\\u0026thinsp;1.75\\u0026ndash;3.62). Associations for gestational diabetes (OR\\u0026thinsp;=\\u0026thinsp;1.15, 95% CI\\u0026thinsp;=\\u0026thinsp;0.69\\u0026ndash;1.94) and severe gall bladder problems (OR\\u0026thinsp;=\\u0026thinsp;2.05, 95% CI\\u0026thinsp;=\\u0026thinsp;0.83\\u0026ndash;5.11) were elevated but not statistically significant. Finally, we did not observe an association between other conditions requiring medical attention and CDS (OR\\u0026thinsp;=\\u0026thinsp;1.03, 95% CI\\u0026thinsp;=\\u0026thinsp;0.61\\u0026ndash;1.76).\\u003c/p\\u003e \\u003cp\\u003e \\u003cem\\u003ePregnancy Complications.\\u003c/em\\u003e The only pregnancy complication that was significantly associated with elevated CDS symptoms in children was heavy bleeding during pregnancy with 60% higher odds of elevated CDS compared with unexposed children (95% CI\\u0026thinsp;=\\u0026thinsp;1.54\\u0026ndash;4.40). Placental problems, birthing parent accident/injury requiring medical attention, and RH incompatibility were related to slightly higher odds of elevated CDS, but associations were not statistically significant.\\u003c/p\\u003e \\u003cp\\u003e \\u003cem\\u003ePrenatal Substance Exposure.\\u003c/em\\u003e Among prenatal substance exposures, birthing parent-reported illicit drug use was related to the highest odds of elevated CDS symptoms (OR\\u0026thinsp;=\\u0026thinsp;2.89, 95% CI\\u0026thinsp;=\\u0026thinsp;2.02\\u0026ndash;4.13). Tobacco exposure (OR\\u0026thinsp;=\\u0026thinsp;1.90, 95% CI\\u0026thinsp;=\\u0026thinsp;1.37\\u0026ndash;2.64) and prescription medication use (OR\\u0026thinsp;=\\u0026thinsp;1.62, 95% CI\\u0026thinsp;=\\u0026thinsp;1.17\\u0026ndash;2.25) were also related to significantly higher odds of clinically elevated CDS. The smallest magnitude association was observed for alcohol use in pregnancy (OR\\u0026thinsp;=\\u0026thinsp;1.12, 95% CI\\u0026thinsp;=\\u0026thinsp;0.83\\u0026ndash;1.52), which was not statistically significant.\\u003c/p\\u003e \\u003cp\\u003e \\u003cb\\u003eDelivery, Birth, and Developmental Milestones (\\u003c/b\\u003eFig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e\\u003cb\\u003e).\\u003c/b\\u003e\\u003c/p\\u003e \\u003cp\\u003e \\u003cem\\u003eDelivery and Birth.\\u003c/em\\u003e We observed the strongest associations between children being reported as blue at birth and not breathing at first, such that exposed children had roughly a 2.5-fold (OR\\u0026thinsp;=\\u0026thinsp;2.57, 95% CI\\u0026thinsp;=\\u0026thinsp;1.49\\u0026ndash;4.41) and 2-fold (OR\\u0026thinsp;=\\u0026thinsp;2.10, 95% CI\\u0026thinsp;=\\u0026thinsp;1.26\\u0026ndash;3.49) higher odds of elevated CDS than unexposed children, respectively. Although children requiring oxygen at birth was also related to a 40% higher odds of clinically elevated CDS compared to unexposed children, this association was not statistically significant. Other significant associations were observed for parent-reported jaundice needing treatment (OR\\u0026thinsp;=\\u0026thinsp;1.88, 95% CI\\u0026thinsp;=\\u0026thinsp;1.36\\u0026ndash;2.59) and child incubation following delivery (OR\\u0026thinsp;=\\u0026thinsp;1.68, 95% CI\\u0026thinsp;=\\u0026thinsp;1.13\\u0026ndash;2.51). Smaller magnitude associations that were not statistically significant included slow heartbeat at birth (OR\\u0026thinsp;=\\u0026thinsp;1.80, 95% CI\\u0026thinsp;=\\u0026thinsp;0.94\\u0026ndash;3.46) and children requiring blood transfusions (OR\\u0026thinsp;=\\u0026thinsp;3.07, 95% CI\\u0026thinsp;=\\u0026thinsp;0.72\\u0026ndash;13.07). We did not observe elevated risk of CDS related to prematurity (OR\\u0026thinsp;=\\u0026thinsp;1.02, 95% CI\\u0026thinsp;=\\u0026thinsp;0.65\\u0026ndash;1.60), low birth weight (OR\\u0026thinsp;=\\u0026thinsp;0.97, 95% CI\\u0026thinsp;=\\u0026thinsp;0.63\\u0026ndash;1.59), or C-section delivery (OR\\u0026thinsp;=\\u0026thinsp;0.91, 95% CI\\u0026thinsp;=\\u0026thinsp;0.68\\u0026ndash;1.23).\\u003c/p\\u003e \\u003cp\\u003e \\u003cem\\u003eDevelopmental Milestones.\\u003c/em\\u003e Children of parents reporting late motor and speech development had significantly higher odds of clinically elevated CDS symptoms, both of which were related to over a 2.5-fold higher odds of elevated CDS (motor OR\\u0026thinsp;=\\u0026thinsp;2.61, 95% CI\\u0026thinsp;=\\u0026thinsp;1.81\\u0026ndash;3.78; speech OR\\u0026thinsp;=\\u0026thinsp;2.56, 95% CI\\u0026thinsp;=\\u0026thinsp;1.91\\u0026ndash;3.43).\\u003c/p\\u003e\"},{\"header\":\"Discussion\",\"content\":\"\\u003cp\\u003eOur study aim was to begin establishing a literature examining the prenatal, perinatal, and early life risks for CDS, a construct that co-occurs with other concerns (e.g., ADHD) with more well-established etiological roots in pregnancy and early development. We estimated bivariate associations between a wide range of early life risk factors and subsequent elevations in CDS symptoms in a large and representative sample of U.S. children using birth parent report of their child\\u0026rsquo;s gestational and developmental histories and CDS symptoms at 9\\u0026ndash;10 years old. Given the dearth of current research in this area, we believe our findings substantially add to the literature and will provide a foundation for research in this area moving forward. Below, we summarize and contextualize our findings with regard for future research needs, beginning with our findings on prenatal substance exposure since this has been the primary focus of prior work. We end with a general discussion of research priorities study limitations.\\u003c/p\\u003e \\u003cp\\u003e \\u003cb\\u003eExpansion of Current Evidence Regarding Prenatal Substance Exposure and CDS.\\u003c/b\\u003e \\u003c/p\\u003e \\u003cp\\u003eOur study is the second that we are aware of to document an association between tobacco exposure in pregnancy and CDS in children. Though Camprodon-Rosanas et al. [\\u003cspan citationid=\\\"CR21\\\" class=\\\"CitationRef\\\"\\u003e21\\u003c/span\\u003e] did not observe a significant association after adjustment for covariates, the study was likely underpowered. However, we did not adjust for covariates given the exploratory aims of the current study, which could also explain differences in findings. In fact, although prenatal tobacco exposure has been robustly associated with fetal growth restriction, prematurity, and small for gestational age [\\u003cspan citationid=\\\"CR45\\\" class=\\\"CitationRef\\\"\\u003e45\\u003c/span\\u003e], which maybe the mechanism by which it influences neurodevelopment [\\u003cspan citationid=\\\"CR6\\\" class=\\\"CitationRef\\\"\\u003e6\\u003c/span\\u003e], there is more mixed evidence regarding whether prenatal tobacco exposure causally contributes to neurodevelopmental outcomes such as ADHD [\\u003cspan additionalcitationids=\\\"CR47\\\" citationid=\\\"CR46\\\" class=\\\"CitationRef\\\"\\u003e46\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR48\\\" class=\\\"CitationRef\\\"\\u003e48\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eAlthough parent-reported alcohol use in pregnancy was related to a 12% higher odds of elevated CDS symptoms compared with unexposed children, this is a comparatively small magnitude association, and the estimate was not statistically significant. Thus, our findings are most consistent with Tsang et al. [\\u003cspan citationid=\\\"CR20\\\" class=\\\"CitationRef\\\"\\u003e20\\u003c/span\\u003e], who found no differences in terms of CDS risk, also measured with the CBCL, though using a different cut off. In contrast, Graham et al. [\\u003cspan citationid=\\\"CR19\\\" class=\\\"CitationRef\\\"\\u003e19\\u003c/span\\u003e], who did observe an association, used a more comprehensive, 15-item (rather than 4 items in the CBCL) CDS measure and estimated the association using a total score rather than a binary cut off.\\u003c/p\\u003e \\u003cp\\u003eParent-reported illicit drug use was related to highest risk of CDS among all the prenatal substance exposures examined. Parent-reported prescription medication use was also related to higher risk for elevated CDS symptoms. However, more work is needed to specify which drugs are associated with CDS, as each drug included in the composite variables has distinct pharmacokinetic and pharmacodynamics properties.\\u003c/p\\u003e \\u003cp\\u003e \\u003cb\\u003eUnplanned Pregnancy, Later Pregnancy Awareness, and Teenage Parenthood May be Proxies for Prenatal Health.\\u003c/b\\u003e \\u003c/p\\u003e \\u003cp\\u003eOur findings regarding higher risk of CDS related to unplanned pregnancies, awareness of pregnancy after 6 weeks, and teenage parenthood warrant further investigation. In addition to examination of possible confounding, such investigations should examine the extent to which these variables may be proxies for 1) a lack of prenatal care or 2) exposure to teratogens or other insults in the absence of birthing parent awareness of pregnancy or education regarding prenatal health, which may be the case for teenage pregnant people without support or resources [\\u003cspan citationid=\\\"CR32\\\" class=\\\"CitationRef\\\"\\u003e32\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR33\\\" class=\\\"CitationRef\\\"\\u003e33\\u003c/span\\u003e]. The prevalence of unplanned pregnancies in the current study is alarmingly high (40.27%), and pregnancy awareness after 6 weeks was prevalent in approximately one fourth (24.77%) of the sample. Although in need of replication and further investigation with regard to CDS specifically, these findings in conjunction with other research [\\u003cspan citationid=\\\"CR31\\\" class=\\\"CitationRef\\\"\\u003e31\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR32\\\" class=\\\"CitationRef\\\"\\u003e32\\u003c/span\\u003e], highlight the importance of equitable access to sex education, contraceptives, and reproductive and prenatal healthcare.\\u003c/p\\u003e \\u003cp\\u003e \\u003cb\\u003ePre- and Perinatal Exposure Indices that Restrict Growth, Nutrients, and Oxygen should be Prioritized in Future Research.\\u003c/b\\u003e \\u003c/p\\u003e \\u003cp\\u003eAmong birthing parent illness, pregnancy complications, and delivery and birth indices, several patterns emerged providing convergent evidence for higher risk of CDS. First, although parent-reported gestational hypertension was modestly (though not significantly) associated with CDS, we observed the highest risk of elevated CDS symptoms pertaining to persistent proteinuria, with exposed children having almost a 10-fold higher odds of CDS compared to unexposed children. In addition, preeclampsia/toxemia was also significantly related to higher risk of elevated CDS symptoms. Given that gestational hypertension is often a precursor to preeclampsia, the latter of which is also often diagnosed when hypertension is present in combination with proteinuria, these findings provide a consistent narrative regarding the severity and progression of these illnesses in conferring risk for CDS\\u0026mdash;or alternatively\\u0026mdash;the importance of considering the confounding factors that may influence and distinguish those who progress from gestational hypertension to more severe conditions from those who do not. It is hypothesized that associations between gestational hypertensive disorders and adverse offspring outcomes may be related to decreased blood flow and oxygen to the placenta [\\u003cspan citationid=\\\"CR49\\\" class=\\\"CitationRef\\\"\\u003e49\\u003c/span\\u003e], which would negatively impact embryonic and fetal growth and access to nutrients and oxygen; these disorders also increase risk of and/or premature labor and delivery [\\u003cspan citationid=\\\"CR49\\\" class=\\\"CitationRef\\\"\\u003e49\\u003c/span\\u003e], which we discuss separately below.\\u003c/p\\u003e \\u003cp\\u003eParent-reported UTI and severe anemia in pregnancy were each associated with approximately 2.5 times higher odds of elevated CDS symptoms compared to children born to parents who did not report these illnesses in pregnancy. These illnesses are also the most common illnesses in pregnancy [\\u003cspan citationid=\\\"CR50\\\" class=\\\"CitationRef\\\"\\u003e50\\u003c/span\\u003e], making further research especially important. Both conditions can also exert effects on placental health and lead to preterm labor [\\u003cspan additionalcitationids=\\\"CR51\\\" citationid=\\\"CR50\\\" class=\\\"CitationRef\\\"\\u003e50\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR52\\\" class=\\\"CitationRef\\\"\\u003e52\\u003c/span\\u003e]. Additionally, one study has found iron-deficiency (a common cause of anemia) in infancy to be associated with later CDS in childhood and adolescence [\\u003cspan citationid=\\\"CR23\\\" class=\\\"CitationRef\\\"\\u003e23\\u003c/span\\u003e], which has implications for nutritional deprivation and possible heritable effects of anemia in relation to CDS symptoms [\\u003cspan citationid=\\\"CR53\\\" class=\\\"CitationRef\\\"\\u003e53\\u003c/span\\u003e]. This is also consistent with our finding over double the odds of elevated CDS symptoms related to parent-reported severe nausea and vomiting beyond 6 months of gestation or accompanied by weight loss, which may also impact fetal access to nutrients.\\u003c/p\\u003e \\u003cp\\u003eIt should be noted that if restriction of fetal growth, nutrients, and/or oxygen were important plausible mechanisms, we might have expected to observe a stronger association for placental problems. Yet, the association was small-magnitude and non-significant. Still, parent-reported heavy bleeding during pregnancy, which is commonly caused by placental problems, was related to higher risk of CDS, and may yet again identify the highest severity placental problems (e.g., significant placental rupture) and confer downstream risk. Furthermore, parent-reported jaundice that required treatment was also related to higher risk for CDS, which can also result from restricted oxygen in utero [\\u003cspan citationid=\\\"CR54\\\" class=\\\"CitationRef\\\"\\u003e54\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR55\\\" class=\\\"CitationRef\\\"\\u003e55\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eHypoxia or lack of oxygen during labor and delivery may be another important avenue for future research as we observed over double the odds of elevated CDS symptoms related to parent reports of their child being blue and not breathing at first upon delivery compared to children whose parents did not report these exposures. We did not observe statistically significant associations for other related indices, such as slow heart beat at birth and children requiring oxygen after birth, though associations were in the same direction, just smaller in magnitude. Finally, incubation after delivery was also associated with higher risk for CDS, which may be related to many of these risk indices.\\u003c/p\\u003e \\u003cp\\u003eAside from those already mentioned, we observed smaller magnitude and non-significant associations for parent-reported severe gall bladder attack, gestational diabetes, Rh incompatibility, and children requiring a blood transfusion after delivery, which may suggest that these indices should be less of a research priority for future investigations of pre- and perinatal risk for elevated CDS symptoms. We also found no elevations in CDS symptoms when comparing children delivered with and without C-section delivery, premature birth, and low birth weight. We discuss prematurity and low birth weight in more detail next.\\u003c/p\\u003e \\u003cp\\u003e \\u003cb\\u003eReplication of Prematurity and Birth Weight Findings in a Sample that Includes Extremely Premature Children is Needed.\\u003c/b\\u003e \\u003c/p\\u003e \\u003cp\\u003eOur study findings and their potential implications regarding investigation of fetal growth and/or premature labor and delivery are complicated by our lack of finding elevated CDS symptoms related to prematurity and low birth weight. For both of these indices, it is important to highlight that a significant limitation of the current study is the exclusion of children born extremely premature (i.e., prior to 28 weeks of gestation), thus truncating the variance of these variables to a significant degree. Indeed, this may explain why we did not replicate findings of Georgsdottir, Haraldsson [\\u003cspan citationid=\\\"CR22\\\" class=\\\"CitationRef\\\"\\u003e22\\u003c/span\\u003e] who observed an association between extremely low birth weight and CDS symptoms during teenage years. Furthermore, we did not have information on gestational age at birth for children that were born at and beyond term, which also limited our ability to examine indices such as small for gestational age. However, we might expect some of the observed associations in the present study to be strengthened by the inclusion of extremely premature infants, since prematurity and fetal growth restriction are one mechanism by which many of these exposures are hypothesized to take effect. Finally, the prevalence of clinically elevated CDS symptoms in the ABCD cohort is lower than in prior research using nationally representative samples, which may again support the notion that the current sample may not be capturing a subset of children at risk for CDS [\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003e \\u003cb\\u003eLate Motor and Speech Development may be Markers for CDS.\\u003c/b\\u003e \\u003c/p\\u003e \\u003cp\\u003eWe observed over a 2.5 times higher odds of elevated CDS symptoms among children whose parents perceived their children to achieve motor and speech milestones later than other children. An important next step for this and for pre- and perinatal health indices will be to rule out the explanation that these associations are only present because of the high co-occurrence between CDS and ADHD (and other neurodevelopmental outcomes).\\u003c/p\\u003e \\u003cp\\u003e \\u003cb\\u003eMethodological Considerations for Future Research.\\u003c/b\\u003e \\u003c/p\\u003e \\u003cp\\u003eIn addition to research on the topics discussed above, we want to highlight some important methodological next steps. First, now that we have a better understanding of which early life risk factors most strongly relate to CDS, the next step is to more rigorously examine whether observed associations might be causal. In addition to covariate adjustment, quasi-experimental designs (e.g., sibling comparisons) and methods commonly used in epidemiology (e.g., active comparators, matching) are especially important to rule out confounding by genetic and other environmental factors. Second, the use of more comprehensive measures of CDS (like those used in Graham et al. [\\u003cspan citationid=\\\"CR19\\\" class=\\\"CitationRef\\\"\\u003e19\\u003c/span\\u003e]) will be critical to properly detect associations, as was recently highlighted in a review identifying key directions for CDS research that also called for more etiologic and early life risk factor research [\\u003cspan citationid=\\\"CR12\\\" class=\\\"CitationRef\\\"\\u003e12\\u003c/span\\u003e]. Third, it will be essential to examine common and unique risk factors for CDS and commonly co-occurring difficulties, including other neurodevelopmental concerns (e.g., autism spectrum disorder).\\u003c/p\\u003e\"},{\"header\":\"Conclusions\",\"content\":\"\\u003cp\\u003eThe current study sought to estimate the magnitude of associations between a broad range of early life risk factors and elevated CDS symptoms in children at 9\\u0026ndash;10 years of age in a large and representative sample of U.S. children, in order to set a research agenda for future work on this topic. We observed initial evidence that warrants further research in many areas, including prenatal substance exposures, other pregnancy conditions and complications that may restrict fetal growth and access to nutrients and oxygen, and achievement of early life developmental milestones. Future research should prioritize examination of the likelihood that these exposure indices causally contribute to CDS.\\u003c/p\\u003e\"},{\"header\":\"Declarations\",\"content\":\"\\u003ch2\\u003eFunding:\\u003c/h2\\u003e \\u003cp\\u003e Dr. Wiggs's effort on this project was supported by the National Research Service Award in Primary Medical Care, T32HP10027, through the Health Resources and Services Administration (HRSA). Isha Lodhawala\\u0026rsquo;s effort on this project was supported in part by funding from the National Institute of Mental Health (R01MH122415) (NIMH). Emma Cleary\\u0026rsquo;s effort on this project was supported by funding from the National Institute on Drug Abuse (NIDA) of the National Institutes of Health Institutional Training Grant T32DA024628-14. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIMH, NIDA, or HRSA.\\u003c/p\\u003e\\u003ch2\\u003eAuthor Contribution\\u003c/h2\\u003e\\u003cp\\u003eK.K.W. was primarily responsible for analytic design, data preparation and cleaning, all analyses, interpretation of findings, and preparation of the manuscript (including tables and figures)T.E.C. contributed to data preparation and cleaning, preliminary analysis, and reviewed the manuscriptI.L. contributed to a literature search, preliminary analysis, and reviewed the manuscriptE.N.C. contributed to analytic design and reviewed the manuscriptK.Y. contributed to analytic design, interpretation of results, and reviewed the manuscriptS.P.B. analytic design, interpretation of results, and reviewed the manuscript\\u003c/p\\u003e\\u003ch2\\u003eAcknowledgement\\u003c/h2\\u003e\\u003cp\\u003eData used in the preparation of this article were obtained from the Adolescent Brain Cognitive Development (ABCD) Study (https://abcdstudy.org), held in the NIMH Data Archive (NDA). This is a multisite, longitudinal study designed to recruit more than 10,000 children age 9-10 and follow them over 10 years into early adulthood. The ABCD Study\\u0026reg; 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, U24DA041147. A full list of supporters is available at https://abcdstudy.org/federal-partners.html. A listing of participating sites and a complete listing of the study investigators can be found at https://abcdstudy.org/consortium_members/. ABCD consortium investigators designed and implemented the study and/or provided data but did not necessarily participate in the analysis or writing of this report. This manuscript reflects the views of the authors and may not reflect the opinions or views of the NIH or ABCD consortium investigators. The ABCD data repository grows and changes over time. The ABCD data used in this report came from [10.15154/bkya-7b87].\\u003c/p\\u003e\\u003ch2\\u003eData Availability\\u003c/h2\\u003e\\u003cp\\u003eThe DOI for this study through the national data archive can be found at https://nda.nih.gov/general-query.html under the following assignment: DOI: 10.15154/z563-zd24\\u003c/p\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\u003cli\\u003e\\u003cspan\\u003eBarker DJP (1998) Mothers, babies and disease in later life. No Title)\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eBarker D, Osmond C (1988) Low birth weight and hypertension. BMJ: Br Med J 297(6641):134\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eBarker DJ (1990) The fetal and infant origins of adult disease. BMJ: Br Med J 301(6761):1111\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eBale TL et al (2010) Early life programming and neurodevelopmental disorders. Biol Psychiatry 68(4):314\\u0026ndash;319\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eNigg JT et al (2020) Development of ADHD: Etiology, heterogeneity, and early life course. Annual Rev Dev Psychol 2:559\\u0026ndash;583\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eKim JH et al (2020) Environmental risk factors, protective factors, and peripheral biomarkers for ADHD: an umbrella review. Lancet Psychiatry 7(11):955\\u0026ndash;970\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eGhirardi L et al (2019) Genetic and environmental contribution to the overlap between ADHD and ASD trait dimensions in young adults: a twin study. Psychol Med 49(10):1713\\u0026ndash;1721\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eVisser JC et al (2016) Autism spectrum disorder and attention-deficit/hyperactivity disorder in early childhood: A review of unique and shared characteristics and developmental antecedents. Neurosci Biobehavioral Reviews 65:229\\u0026ndash;263\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eAndersson A et al (2020) Research Review: The strength of the genetic overlap between ADHD and other psychiatric symptoms\\u0026ndash;a systematic review and meta-analysis. J Child Psychol Psychiatry 61(11):1173\\u0026ndash;1183\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003ePettersson E et al (2013) Different neurodevelopmental symptoms have a common genetic etiology. J Child Psychol Psychiatry 54(12):1356\\u0026ndash;1365\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eBarkley RA (2013) Distinguishing sluggish cognitive tempo from ADHD in children and adolescents: executive functioning, impairment, and comorbidity. J Clin Child Adolesc Psychol 42(2):161\\u0026ndash;173\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eBecker SP et al (2023) Report of a work group on sluggish cognitive tempo: Key research directions and a consensus change in terminology to cognitive disengagement syndrome. J Am Acad Child Adolesc Psychiatry 62(6):629\\u0026ndash;645\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eBurns GL, Becker SP (2021) Sluggish cognitive tempo and ADHD symptoms in a nationally representative sample of US children: Differentiation using categorical and dimensional approaches. J Clin Child Adolesc Psychol 50(2):267\\u0026ndash;280\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eServera M et al (2018) Clinical differentiation of sluggish cognitive tempo and attention-deficit/hyperactivity disorder in children. J Abnorm Psychol 127(8):818\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eNeeper R, Lahey BB (1986) The Children's Behavior Rating Scale: A factor analytic developmental study. School Psychol Rev 15(2):277\\u0026ndash;288\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eLahey BB et al (1988) Dimensions and types of attention deficit disorder. J Am Acad Child Adolesc Psychiatry 27(3):330\\u0026ndash;335\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eBecker SP et al (2016) The internal, external, and diagnostic validity of sluggish cognitive tempo: A meta-analysis and critical review. J Am Acad Child Adolesc Psychiatry 55(3):163\\u0026ndash;178\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eBurns GL et al (2024) Clinical distinction between cognitive disengagement syndrome and ADHD presentations in a nationally representative sample of Spanish children and adolescents. Journal of Child Psychology and Psychiatry\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eGraham DM et al (2013) Prenatal alcohol exposure, attention-deficit/hyperactivity disorder, and sluggish cognitive tempo. Alcoholism: Clin Experimental Res 37:E338\\u0026ndash;E346\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eTsang TW et al (2017) Behavior in children with fetal alcohol spectrum disorders in remote Australia: a population-based study. J Dev Behav Pediatr 38(7):528\\u0026ndash;537\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eCamprodon-Rosanas E et al (2017) Sluggish cognitive tempo: Sociodemographic, behavioral, and clinical characteristics in a population of Catalan school children. J Atten Disord 21(8):632\\u0026ndash;641\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eGeorgsdottir I, Haraldsson A, Dagbjartsson A (2013) Behavior and well-being of extremely low birth weight teenagers in Iceland. Early Hum Dev 89(12):999\\u0026ndash;1003\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eEast PL et al (2023) Iron deficiency in infancy and sluggish cognitive tempo and ADHD symptoms in childhood and adolescence. J Clin Child Adolesc Psychol 52(2):259\\u0026ndash;270\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eHeeringa SG, Berglund PA (2020) \\u003cem\\u003eA guide for population-based analysis of the Adolescent Brain Cognitive Development (ABCD) Study baseline data.\\u003c/em\\u003e BioRxiv, : p. 2020.02. 10.942011\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eGaravan H et al (2018) Recruiting the ABCD sample: Design considerations and procedures. Dev Cogn Neurosci 32:16\\u0026ndash;22\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003ePaul SE et al (2021) Associations between prenatal cannabis exposure and childhood outcomes: results from the ABCD study. JAMA psychiatry 78(1):64\\u0026ndash;76\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eMoreau AL et al (2023) Prenatal selective serotonin reuptake inhibitor exposure, depression, and brain morphology in middle childhood: results from the ABCD study. Biol Psychiatry Global Open Sci 3(2):243\\u0026ndash;254\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eDooley N et al (2022) Birth weight and childhood psychopathology in the ABCD cohort: association is strongest for attention problems and is moderated by sex. Res Child Adolesc Psychopathol 50(5):563\\u0026ndash;575\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eDooley N et al (2023) Explaining the association between fetal growth and childhood ADHD symptoms: Cross-cohort replication. Res Child Adolesc Psychopathol 51(2):247\\u0026ndash;259\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eWiggs KK et al (2022) Maternal serotonergic antidepressant use in pregnancy and risk of seizures in children. Neurology 98(23):e2329\\u0026ndash;e2336\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eWiggs KK et al (2020) Antiseizure medication use during pregnancy and risk of ASD and ADHD in children. Neurology 95(24):e3232\\u0026ndash;e3240\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eGoossens J et al (2016) The prevalence of unplanned pregnancy ending in birth, associated factors, and health outcomes. Hum Reprod, : p. 1\\u0026ndash;13\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eBranum AM, Ahrens KA (2017) Trends in timing of pregnancy awareness among US women. Matern Child Health J 21:715\\u0026ndash;726\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eBaker BH et al (2023) Maternal age at birth and child attention-deficit hyperactivity disorder: causal association or familial confounding? J Child Psychol Psychiatry 64(2):299\\u0026ndash;310\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eDu J et al (2022) Association between parental age, brain structure, and behavioral and cognitive problems in children. Mol Psychiatry 27(2):967\\u0026ndash;975\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eLean SC et al (2017) Advanced maternal age and adverse pregnancy outcomes: A systematic review and meta-analysis. PLoS ONE 12(10):e0186287\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eZhang C, Yan L, Qiao J (2022) Effect of advanced parental age on pregnancy outcome and offspring health. J Assist Reprod Genet 39(9):1969\\u0026ndash;1986\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eMin X, Li C, Yan Y (2021) Parental age and the risk of ADHD in offspring: a systematic review and meta-analysis. Int J Environ Res Public Health 18(9):4939\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eMomany AM, Kamradt JM, Nikolas MA (2018) A meta-analysis of the association between birth weight and attention deficit hyperactivity disorder. J Abnorm Child Psychol 46:1409\\u0026ndash;1426\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eZhuo H et al (2022) Developmental Milestones of Infancy and Associations with Later Childhood Neurodevelopmental Outcomes in the Adolescent Brain Cognitive Development (ABCD) Study. Children 9(10):1424\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003e\\u003cem\\u003eManual for the ASEBA preschool forms and profiles\\u003c/em\\u003e. Vol. 30. 2000: Burlington, VT: University of Vermont, Research center for children,youth \\u0026amp;#8230\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eSkirbekk B et al (2011) The relationship between sluggish cognitive tempo, subtypes of attention-deficit/hyperactivity disorder, and anxiety disorders. J Abnorm Child Psychol 39(4):513\\u0026ndash;525\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eBurns GL, Becker SP (2022) Convergent and discriminant validity of the Child and Adolescent Behavior Inventory Scale scores with well-established psychopathology and academic achievement measures in adolescents with ADHD. Assessment 29(5):1086\\u0026ndash;1098\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eIBM Corp Released 2019. IBM SPSS Statistics for Windows, Version 26.0. Armonk, NY: IBM Corp\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eMoore KL, Persaud TVN, Torchia MG (2018) The Developing Human-E-Book: The Developing Human-E-Book. Elsevier Health Sciences\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eD'Onofrio BM et al (2008) Smoking during pregnancy and offspring externalizing problems: an exploration of genetic and environmental confounds. Dev Psychopathol 20(1):139\\u0026ndash;164\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eSkoglund C et al (2014) Familial confounding of the association between maternal smoking during pregnancy and ADHD in offspring. J Child Psychol Psychiatry 55(1):61\\u0026ndash;68\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eKnopik VS et al (2016) Smoking during pregnancy and ADHD risk: A genetically informed, multiple-rater approach. Am J Med Genet Part B: Neuropsychiatric Genet 171(7):971\\u0026ndash;981\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eMaher GM et al (2018) Association of hypertensive disorders of pregnancy with risk of neurodevelopmental disorders in offspring: a systematic review and meta-analysis. JAMA psychiatry 75(8):809\\u0026ndash;819\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eSzweda H, J\\u0026oacute;źwik M (2016) Urinary tract infections during pregnancy-an updated overview. Dev Period Med 20(4):263\\u0026ndash;272\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eLelic M et al (2014) Influence of maternal anemia during pregnancy on placenta and newborns. Med Archives 68(3):184\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eRoberts H, Bourque SL, Renaud SJ (2020) Maternal iron homeostasis: effect on placental development and function. Reproduction 160(4):R65\\u0026ndash;R78\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eBarrera-Reyes PK, Tejero ME (2019) Genetic variation influencing hemoglobin levels and risk for anemia across populations, vol 1450. Annals of the New York Academy of Sciences, pp 32\\u0026ndash;46. 1\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eDani C et al (2018) Changes in bilirubin in infants with hypoxic\\u0026ndash;ischemic encephalopathy. Eur J Pediatrics 177:1795\\u0026ndash;1801\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eMitra S, Rennie J (2017) Neonatal jaundice: aetiology, diagnosis and treatment. Br J Hosp Med 78(12):699\\u0026ndash;704\\u003c/span\\u003e\\u003c/li\\u003e\\u003c/ol\\u003e\"}],\"fulltextSource\":\"\",\"fullText\":\"\",\"funders\":[],\"hasAdminPriorityOnWorkflow\":false,\"hasManuscriptDocX\":true,\"hasOptedInToPreprint\":true,\"hasPassedJournalQc\":\"\",\"hasAnyPriority\":false,\"hideJournal\":false,\"highlight\":\"\",\"institution\":\"\",\"isAcceptedByJournal\":true,\"isAuthorSuppliedPdf\":false,\"isDeskRejected\":\"\",\"isHiddenFromSearch\":false,\"isInQc\":false,\"isInWorkflow\":false,\"isPdf\":false,\"isPdfUpToDate\":true,\"isWithdrawnOrRetracted\":false,\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"european-child-and-adolescent-psychiatry\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"ecap\",\"sideBox\":\"Learn more about [European Child \\u0026 Adolescent Psychiatry](http://link.springer.com/journal/787)\",\"snPcode\":\"787\",\"submissionUrl\":\"https://submission.nature.com/new-submission/787/3\",\"title\":\"European Child \\u0026 Adolescent Psychiatry\",\"twitterHandle\":\"\",\"acdcEnabled\":true,\"dfaEnabled\":true,\"editorialSystem\":\"em\",\"reportingPortfolio\":\"Springer Hybrid\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":false},\"keywords\":\"prenatal risk, perinatal risk, early life risk, cognitive disengagement syndrome, sluggish cognitive tempo\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-4468007/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-4468007/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003ch2\\u003eBackground.\\u003c/h2\\u003e \\u003cp\\u003eLittle research has examined early life risk for symptoms of cognitive disengagement syndrome (CDS) despite a well-established literature regarding co-occurring outcomes (e.g., attention-deficit/hyperactivity disorder). The current study estimated bivariate associations between early life risk factors and CDS in a large and representative sample of U.S. children.\\u003c/p\\u003e\\u003ch2\\u003eMethods.\\u003c/h2\\u003e \\u003cp\\u003eWe conducted secondary analyses of baseline data from the Adolescent Brain Cognitive Development (ABCD) study (N\\u0026thinsp;=\\u0026thinsp;8,096 children, 9\\u0026ndash;10 years old). Birthing parents reported early life risk factors on a developmental history questionnaire, including parental, prenatal, delivery and birth, and developmental milestone information. They also completed the Child Behavior Checklist, which includes a CDS subscale that was dichotomized to estimate the odds of elevated CDS symptoms (i.e., \\u003cem\\u003eT-\\u003c/em\\u003escore\\u0026thinsp;\\u0026gt;\\u0026thinsp;70) in children related to risk indices.\\u003c/p\\u003e\\u003ch2\\u003eResults.\\u003c/h2\\u003e \\u003cp\\u003eWe observed significantly elevated odds of CDS related to parental risk factors (i.e., unplanned pregnancy, pregnancy awareness after 6 weeks, teenage parenthood), birthing parent illnesses in pregnancy (i.e., severe nausea, proteinuria, pre-eclampsia/toxemia, severe anemia, urinary tract infection), pregnancy complications (i.e., bleeding), prenatal substance exposures (i.e., prescription medication, tobacco, illicit drugs), delivery and birth risk factors (i.e., child blue at delivery, child not breathing, jaundice, incubation after delivery), and late motor and speech milestones in children.\\u003c/p\\u003e\\u003ch2\\u003eConclusions.\\u003c/h2\\u003e \\u003cp\\u003eSeveral early-life risk factors were associated with elevated odds of CDS at ages 9\\u0026ndash;10 years; study design prevents the determination of causality. Further investigation is warranted regarding early life origins of CDS with priority given to risk indices that have upstream commonalities (i.e., that restrict fetal growth, nutrients, and oxygen).\\u003c/p\\u003e\",\"manuscriptTitle\":\"Setting a research agenda for examining early risk for elevated cognitive disengagement syndrome symptoms using data from the ABCD cohort\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2024-06-10 22:21:06\",\"doi\":\"10.21203/rs.3.rs-4468007/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0},{\"type\":\"decision\",\"content\":\"Revision requested\",\"date\":\"2024-11-09T23:26:12+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorInvitedReview\",\"content\":\"\",\"date\":\"2024-11-09T22:58:33+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"editorInvitedReview\",\"content\":\"\",\"date\":\"2024-07-23T10:15:02+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"95305626916369412560240828987009650215\",\"date\":\"2024-07-15T22:39:31+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"230815994326022438240743419887418967059\",\"date\":\"2024-07-15T15:38:52+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewersInvited\",\"content\":\"\",\"date\":\"2024-05-24T10:10:22+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"checksComplete\",\"content\":\"\",\"date\":\"2024-05-24T02:36:17+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorAssigned\",\"content\":\"\",\"date\":\"2024-05-24T02:36:17+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"submitted\",\"content\":\"European Child \\u0026 Adolescent Psychiatry\",\"date\":\"2024-05-23T15:50:48+00:00\",\"index\":\"\",\"fulltext\":\"\"}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"european-child-and-adolescent-psychiatry\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"ecap\",\"sideBox\":\"Learn more about [European Child \\u0026 Adolescent Psychiatry](http://link.springer.com/journal/787)\",\"snPcode\":\"787\",\"submissionUrl\":\"https://submission.nature.com/new-submission/787/3\",\"title\":\"European Child \\u0026 Adolescent Psychiatry\",\"twitterHandle\":\"\",\"acdcEnabled\":true,\"dfaEnabled\":true,\"editorialSystem\":\"em\",\"reportingPortfolio\":\"Springer Hybrid\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":false}}],\"origin\":\"\",\"ownerIdentity\":\"ed63a43f-f97a-404c-83f4-e0da89e97c25\",\"owner\":[],\"postedDate\":\"June 10th, 2024\",\"published\":true,\"recentEditorialEvents\":[],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"published-in-journal\",\"subjectAreas\":[],\"tags\":[],\"updatedAt\":\"2025-03-17T15:59:56+00:00\",\"versionOfRecord\":{\"articleIdentity\":\"rs-4468007\",\"link\":\"https://doi.org/10.1007/s00787-025-02667-z\",\"journal\":{\"identity\":\"european-child-and-adolescent-psychiatry\",\"isVorOnly\":false,\"title\":\"European Child \\u0026 Adolescent Psychiatry\"},\"publishedOn\":\"2025-03-10 15:57:09\",\"publishedOnDateReadable\":\"March 10th, 2025\"},\"versionCreatedAt\":\"2024-06-10 22:21:06\",\"video\":\"\",\"vorDoi\":\"10.1007/s00787-025-02667-z\",\"vorDoiUrl\":\"https://doi.org/10.1007/s00787-025-02667-z\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-4468007\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-4468007\",\"identity\":\"rs-4468007\",\"version\":[\"v1\"]},\"buildId\":\"qtupq5eGEP_6zYnWcrvyt\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}