Children with inattentive presentation showed lower adherence (12.2%) to a healthy pattern than that of the control group (39.9%) (p < 0.001). There is an association between ADHD and dietary habits; children with inattentive presentation may particularly be at risk of unhealthy eating habits.Attention-deficit/hyperactivity disorder (ADHD) is one of the most common neurodevelopmental disorders in children and adolescents. A current area of interest is the association between ADHD and food consumption. The aim of this study was to determine the food consumption and dietary patterns of children with and without ADHD in relation to their age and ADHD presentation. The study involved 259 preschoolers aged 3 to 6 years old (57 with ADHD and 202 controls) and 475 elementary-school-age children, aged 10 to 12 years old (213 with ADHD and 262 controls) from Spain. ADHD was diagnosed in accordance with the Diagnostic and Statistical Manual of Mental Disorders (5th edition) from Schedule for Affective Disorders and Schizophrenia for School-Age Children interviews. Eating data were collected using a food consumption frequency questionnaire, and principal component analysis was carried out to analyze dietary patterns. Western-like, sweet, and healthy patterns were identified. The ADHD group was negatively associated with the healthy pattern ( Attention-deficit/hyperactivity disorder (ADHD) is one of the most common neurodevelopmental disorders in children and adolescents. A recent systematic review established the global prevalence of ADHD to be between 2% and 7% . HoweverThe cause of ADHD is unclear. While genetic factors  play an 2 [Associations between nutritional status and ADHD in children have also been analyzed. In this regard, dietary factors have been examined for their possible role in the etiology and treatment of this disorder. Some studies found altered levels of certain oligo elements such as magnesium, iron, and zinc in serum in children with ADHD ,13,14,152 . In Spai2 ,35. They2 , psychol2 ,38, sex 2 , pharmac2 , intelli2 , and ASDIn the present study, we aim to determine the type of diet in a sample of Spanish children with ADHD from two age groups: preschool and elementary school age. First, we analyze the food consumption of children with ADHD in comparison with their control peers and with the dietary guidelines for their age group. Second, we describe the dietary patterns of children with ADHD in relation to ADHD presentations in comparison with those of the control participants. We study differences according to age and the presentation of ADHD in relation to variables that may affect their eating habits, such as sex, parents’ educational level and profession (PELP), pharmacological treatment, intellectual quotient (IQ), internalizing problems, and the presence of any autism spectrum disorder (ASD) comorbidity. We hypothesize that children with ADHD have a low-quality diet with a lower intake of fruits and vegetables than that of their peers without the disorder, and that this shows up specifically in children with combined or hyperactive–impulsive (H–I) ADHD presentations. Moreover, we hypothesize that food consumption generally differs from the established recommendations by dietary guidelines.n = 3727). In the second phase, children at risk and a control group without risk  were individually assessed by trained clinicians to confirm ADHD and ASD diagnoses according to the criteria of the Diagnostic and Statistical Manual of Mental Disorders (5th edition) (DSM-5). Participants received a positive diagnosis of ADHD  when information in the K-SADS-PL interview met the DSM-5 criteria for any of the three presentations of ADHD . Two children who had been diagnosed were considered to have clinical ADHD, although they were in partial remission from symptoms due to pharmacological or psychological treatment. Participants were considered to have subclinical ADHD when they scored positive on parent and teacher Conners’ 10-item indices (T ≥ 65) and presented on the Schedule for Affective Disorders and Schizophrenia for School-Age Children (K-SADS-PL) [The participants in this study come from two research projects carried out in Spain: the Neurodevelopmental Disorders Epidemiological Research Project (EPINED) and the characterization of the metabolic profile  in children and adolescents with ADHD and evaluation of its value as a diagnostic marker (MetigenADHD). EPINED was a two-phase study carried out between 2014 and 2019 with the main aim of estimating the prevalence of ADHD and autism spectrum disorder (ASD) in the school population (preschoolers and elementary-school children) of the province of Tarragona, Catalonia, Spain. In the first phase, the risk of both disorders was screened by validated tests administered by parents and teachers (SADS-PL)  four or SADS-PL) . The MetFor the ADHD diagnosis, the K-SADS-PL semistructured diagnostic interview was administered to the parents. Two instruments were used to diagnose ASD: the Autism Diagnostic Observation Schedule (2nd edition) (ADOS-2)  and the Data on the participants’ eating habits were collected by their parents using two different food consumption frequency questionnaires (FCFQ), with one validated for preschool children (41 items ) and anoThe dietary guidelines of the Spanish Society of Community Nutrition (SENC)  were useThe Spanish Quality Diet Index (SQDI)  was usedPrincipal component analysis (PCA) following general procedures was used to identify the dietary pattern . ® stadiometer, accurate to 0.1 mm (PERILB-STND), was used to measure height (cm), and TANITA scales (BC 420SMA) were used to measure weight (kg). Then, body mass index (BMI)(Kg/m2) and the BMI z score were calculated on the basis of the World Health Organization Child Growth Standards [A dietitian certified by the International Society for the Advancement of Kinanthropometry (ISAK) took the anthropometric measurements. A SECAtandards . Sociodemographic data were reported by parents, and parents’ education level and profession (PELP) were calculated by adapting the Hollingshead  index foTo describe the study sample, variables were compared by age group (preschool and elementary school) and diagnosis . t-test was used instead of ANOVA. Lastly, we carried out ANCOVA, adjusting for our control variables. ANOVA was used to analyze food intake in grams for each diagnosis  and for each age group. No differences were found between diagnosis  or presentations, so the ADHD group was created from clinical and subclinical subgroups. For the food intake per servings analysis, in addition to the diagnosis groups, we combined the two age groups. In this case, the number of servings is the same for both age groups but the grams per intake is not. After combining the groups for both analyses, Student’s t-test analysis were performed to assess associations between the dietary patterns and the different groups in diagnostic categories (a) ADHD diagnoses (ADHD vs control) and (b) with ADHD presentation  and combined). ANCOVA was used to adjust for covariates that may be related to food consumption: sex, PELP, internalizing problems, pharmacological treatment, IQ, and ASD comorbidity. Chi-squared analyses were performed to identify the level of participant adherence to each dietary pattern. Control for multiple testing with Bonferroni correction was performed within the ANOVA, ANCOVA, and chi-squared tests. A 95% confidence interval was provided for all estimations. Statistical analyses were performed using IBM SPSS 27.PCA was used to identify the dietary patterns. First, FCFQ items were grouped into the 20 food groups presented later in the Results section. In the analytical process, we used similar parameters to those in other studies of dietary patterns . ConsumeFood consumption in grams and servings was calculated for the three diagnosis groups, and no differences were shown between the clinical and subclinical groups, or between presentations of ADHD. For these reasons, food consumption was recalculated after combining the ADHD groups . p = 0.033), which was higher in the control group. In both graphs, minimal and maximal servings recommended by the public administration are expressed by dots and asterisks, respectively, except for those foods that should not be eaten or should be eaten occasionally, for which there is no recommendation. Only the consumption of protein foods in general, dairy products , and fish agreed with the experts’ recommendations.To compare food consumption with SENC recommendations, the two age groups were combined because the servings were the same for both. p = 0.905). In the elementary-school-age group, 92.30% of the children with ADHD and 92.40% of the control group also needed to improve (p = 0.992) , raw vegetables, fresh fruit, and olive oil. Lastly, they were ranked and converted into tertiles to analyze adherence.p = 0.004). Among presentations, only ‘inattentive’ had a higher score than that of the control group (p = 0.004). The Healthy pattern had a higher score in the control group than that in the ADHD group (p < 0.001). p < 0.001) than the ADHD group did (22.2%). Among the presentations, the inattentive type showed the lowest adherence (45.9%) to that pattern (p < 0.001). In contrast, no significant differences were found for the Western-like and sweet dietary patterns.This study provided us with knowledge about how children with ADHD and its presentations in two age groups eat in comparison with their control peers and about their adherence to the dietary guidelines. It allowed for us to demonstrate that children with ADHD, and especially the inattentive presentation, had a less healthy diet than the children in the control group did. However, all participants needed to improve their diet because they did not follow the established dietary recommendations.We considered two age groups on the basis that they would present differences in the consolidation of habits. Furthermore, in young children such as preschoolers, there is usually a higher proportion of hyperactivity, which decreases with age , while iRegarding the daily and weekly servings of food consumption, our sample only respected the SENC  recommenResults of the food consumption comparisons did not provide any conclusions about the quality of our participants’ diets. The quality of the diet is not only determined by the consumption of some food or group of foods, but by way of eating while following a dietary pattern. Tucker  also staAs far as dietary patterns are concerned, PCA results showed three main ways of eating, which we named Sweet, Healthy, and Western-like. In the latter case, it is important to say Western-like and not simply Western because this pattern also contains healthy foods, such as cooked vegetables and legumes. Traditionally, in this region, cooked vegetables are usually eaten with boiled potatoes and legumes with some processed meat, a fact that may drag this healthy food into the Western-like pattern. In line with studies by Abbasi et al. , and HowAs far as the Healthy pattern is concerned, our results agree with those of Abbasi et al. , Dong WoAfter analysis, we did not find any differences for the Sweet pattern between the ADHD and the control groups, or for the H–I and combined presentations, as we expected. As previously mentioned, the use of stimulant drugs could relieve the craving for sweets. In this regard, 72.88% of the medicated children  presented the H–I and combined presentation. However, we did not find any differences after adjusting for pharmacological treatment. In agreement with our results, Bowling et al.  found thIn contrast to our findings, Azadbakht and Esmaillzadeh  concludeA strength of this study is the large number of participants composing a representative sample of the Spanish child population and the different ADHD presentations. Furthermore, psychological and nutritional assessment was performed by rigorous and validated methodologies. In terms of limitations, the fact that is not a longitudinal study did not allow for us to determine the directionality of the relation and see whether the diet helps or aggravates the symptomatology of ADHD. Although FCFQ is a great tool that gave us many useful data, a three-day record questionnaire and nutritional biochemistry profiles could give us additional and more realistic information about the children’s feeding process. In addition, this information was reported by external observers, these being either the parents or legal guardians because of the participants’ age. Elementary-school-age children, mostly those with ADHD, could consume unhealthy foods such as sweets and not tell their parents, meaning that it would not have been recorded, leading to a possible reporting bias.The ADHD group, especially the inattentive presentation, adhered less to the Healthy pattern than the control group did, and it was positively associated with the Western-like pattern. The control group had the highest adherence to the Healthy pattern. However, the two groups had a similar adherence to the Sweet dietary pattern. This, the recommended servings comparison, and the SDQI results show that the study population generally has a poor-quality diet that it needs to improve to prevent future health issues.


Attention-deficit/hyperactivity disorder (ADHD) is commonly accompanied by functional impairments within personal, professional, and social context as well as further psychological distress. The role of perceived stress has been examined in this regard, although little is known about the influence of stress coping strategies. We examined the dynamics between ADHD symptomatology, stress coping strategies, and life impairments in a sample of 230 clinical and non-clinical adult individuals. ADHD was associated with low probability of choosing adaptive but high probability of implementing maladaptive stress coping strategies as well as with increased life impairments. Adaptive stress coping showed little effects beyond the associations between ADHD and life impairments, whereas some maladaptive coping strategies increased current life impairments over and above the effects of ADHD and further psychological distress. The present findings emphasize the need of professional support in adults with ADHD and the necessity to include stress coping strategies in respective treatment approaches aimed at reducing life impairments.The online version contains supplementary material available at 10.1007/s00702-021-02311-5. Attention-deficit/hyperactivity disorder (ADHD) ranges among the most common psychiatric disorders in children and adolescents with world-wide prevalence estimations between 5 and 9%  crime involvement and mortality, and to report greater problems in daily life and lower overall quality of life Barkley . DifferePerceived stress both in childhood and adulthood has been claimed to be an important factor associated with ADHD that contributes to elevated risk of comorbid disorders and further impairments  with a mean age of 34.63 years  and an average IQ of 107.88 . Data were collected from a sample of adults from our ADHD outpatient consultation department for clarification of possible ADHD diagnosis  as well as further participants (without suspicion of ADHD diagnosis) recruited on personal demand by the authors . Study procedures were performed in accordance with the ethical standards of the Declaration of Helsinki. Participants were informed about study procedures and goals, voluntary participation, as well as anonymization of data. Written consent was provided.The present study included data of 230 participants . Current ADHD symptomatology was assessed by the ADHD-SB, a self-rating questionnaire affiliated to the Homburger ADHD scales for adults . Childhood ADHD was assessed by the WURS-k, another self-rating questionnaire affiliated to the Homburger ADHD scales for adults . The German stress coping questionnaire . The German version of the SCL-90-R . To account for possible confounding due to general cognitive capability, participants took a short intelligence test in the form of the MWT-B  and, for linear variables, t tests  as well as MANOVAs with post hoc Bonferroni or Games–Howell tests  respecting potential interdependencies among variables. Partial eta-squared  exceeded the WURS-k cut-off value of 30 points, thus indicating clinically relevant ADHD symptomatology in their childhoods. Of those, 105 (98.1%) participants had been referred from our ADHD outpatient consultation department. Moreover, 58.7% (n = 135) of all participants reported clinically relevant, current ADHD symptomatology (ADHD-SB score ≥ 15). Again, the majority of them  came from our ADHD outpatient consultation department. For further analyses, we considered those participants to display a categorical ADHD index group who reported clinically relevant ADHD symptomatology both in childhood and at the current point in time . ADHD and non-ADHD groups differed dimensionally on both ADHD-SB score  = 377.54), p ≤ 0.001, ηp2 = 0.62, and WURS-k score , F = 488.00, p ≤ 0.001, ηp2 = 0.68. ADHD and non-ADHD subjects did not differ with respect to sex distribution, χ2 (1) = 0.04, p = 0.837, mean age, t(227.41) = 0.74, p = 0.461, or IQ, t(282) = 1.76, p = 0.08.Concerning ADHD, 46.5% of the total sample  psychological distress (SCL-90-R) compared to non-ADHD subjects. ADHD severity proved to be a consistent predictor of increased impairments over and above the effects of age, sex, IQ, further (comorbid) psychological distress, and stress coping strategies. These results are in line with those of previous research  psychological distress. However, independent of ADHD severity, the implementation of some maladaptive strategies, e.g., escape, resignation, and social withdrawal, appeared to increase life impairments, whereas some adaptive strategies, e.g., minimization, reaction control, and positive self-instructions, tended toward the reduction of life impairments, especially related to social contexts. These findings emphasize the need to counteract maladaptive stress coping and foster the implementation of adaptive stress coping strategies to reduce life impairments. Yet, as we did not find any interactions in terms of buffering or intensifying impacts of stress coping strategies on the associations between ADHD severity and life impairments (contrary to our expectations), the potential interdependency of ADHD and stress coping strategies for reducing or increasing life impairments remains a subject for further research. Still, it is imperative to include and promote the acquirement of adaptive stress coping strategies in the treatment of adults with ADHD to break through the above-mentioned vicious cycle of perceived stress and ADHD, and offer functional means to reduce the risk of further life impairments.Several strengths and some limitations must be considered when interpreting the current findings. As demanded by previous research  appeared to increase current life impairments. With respect to the potential long-term risks related to maladaptive coping, the acquirement and adequate application of adaptive stress coping strategies is of major importance for individuals with ADHD. Thus, studies and, especially, practitioners working with individuals with ADHD must not neglect to assess their clients’ perceived stress and the coping strategies already in use, but need to provide them with respective treatment approaches that support them in the successful implementation of stress-reducing techniques.Supplementary file1 (DOCX 26 KB)Supplementary file2 (DOCX 26 KB)Supplementary file3 (DOCX 26 KB)Below is the link to the electronic supplementary material.


Low- and middle-income countries rely on household surveys for birthweight data. These data are frequently incomplete and exhibit strong “heaping.” Standard survey adjustment methods produce estimates with residual bias. The global database used to report against the LBW Global Nutrition Target adjusts survey data using a new MINORMIX  approach: To evaluate the performance of the MINORMIX birthweight adjustment approach and alternative methods against gold-standard measured birthweights in rural Nepal.1) the new MINORMAX approach; 2) the previously used Blanc–Wardlaw adjustment; or 3) no adjustment for missingness or heaping against our gold standard. We also assessed the independent contribution of multiple imputation and curve fitting to LBW adjustment.As part of a community-randomized trial in rural Nepal, we measured “gold-standard” birthweights at birth and returned 1–24 mo later to collect maternally reported birthweights using standard survey methods. We compared estimates of LBW from maternally reported data derived using: Our gold standard found 27.7% of newborns were LBW. The unadjusted LBW estimate based on maternal report with simulated missing birthweights was 14.5% . Application of the Blanc–Wardlaw adjustment increased the LBW estimate to 20.6%. The MINORMIX approach produced an estimate of 26.4%  LBW, closest to and with bounds encompassing the measured point estimate.In a rural Nepal validation dataset, the MINORMIX method generated a more accurate LBW estimate than the previously applied adjustment method. This supports the use of the MINORMIX method to produce estimates for tracking the LBW Global Nutrition Target. Low birthweight (LBW) is closely associated with a higher risk of neonatal death as well as cognitive and developmental impairment and long-term health problems in adulthood . The terPopulation-based household surveys, like the Demographic and Health Surveys (DHS) and the Multiple Indicator Cluster Surveys (MICS), are the primary source of birthweight data in most LMIC. These surveys capture birthweight data either through reviewing official records  or, when not available, by maternal report . HoweverUsing birthweight data from 88 DHS datasets, Blanc and Wardlaw  developeThe Lancet Low Birthweight Investigator Group, comprised of members from UNICEF, WHO, the London School of Hygiene and Tropical Medicine, and the Johns Hopkins Bloomberg School of Public Health, recently developed a new approach to adjust estimates of LBW calculated from household survey data for use in the global database to track the LBW Global Nutrition Target . Extendi1) the crude unadjusted estimate as would be reported in a DHS report, and 2) the Blanc and Wardlaw method used in the previous global database, to gauge whether the MINORMIX approach offers a substantial improvement over existing methods. Finally, we assess the relative contribution of the 2 components of the MINORMIX method to the overall performance of the approach, specifically 1) MI of missing birthweights, and 2) fitting a normal model to account for heaping.In this article, we evaluate the MINORMIX approach described above using a household survey dataset of maternal reports of birthweight against that of gold-standard paired measured birthweights collected as part of a large community-randomized trial in rural Nepal. We also assess the performance of the MINORMIX method relative to alternative LBW estimation methods, including The study was carried out in the rural district of Sarlahi, Nepal. This district is in the terai region (plains) along the border with Bihar, India. A little more than one-third of women aged ≥15 y can read and write . Over onThe parent trial and the substudy both received ethical approval from the Johns Hopkins Bloomberg School of Public Health Institutional Review Board, Baltimore, MD, USA. Local approval was received from the Tribhuvan University Institute of Medicine, Kathmandu, Nepal, for the parent trial and from the Nepal Health Research Council, Kathmandu, Nepal, for the substudy.clinicaltrials.gov as NCT01177111). Locally resident female project workers visited married women aged 15–35 y at home every 5 wk to identify new pregnancies; pregnancies in women outside this age range were identified informally. Women who consented to participate were followed through delivery. Study staff visited as soon as possible after delivery, typically within 48 h, but visits conducted ≤72 h after birth were included in our substudy. At the first visit after birth, workers recorded the median of 3 measures of the baby's weight using a digital scale graduated to 10 g (Tanita BD-585) in addition to other data on the circumstances of the birth. These data serve as our gold-standard measure of each study subject's true birthweight. The date, time of birth, and weight of the newborn were also provided to the mother/caretaker on a small card.A randomized community-based trial, conducted from November 2010 to January 2017, examined the impact of the use of sunflower seed oil in full-body newborn massage on neonatal deaths and infections (registered at 1) weight data were collected >72 h after birth, 2) covariates required for the analysis were missing, or 3) the mother had previously been included in the study for another birth. Pairs were excluded from the final analysis if measured birthweight data were unavailable. Study staff requested participation in the homes of selected mothers, administered oral consent in Nepali or Maithili , and obtained a signature or thumbprint for those who agreed to participate. Specific to this analysis, mothers were asked standard questions from the DHS or MICS including birthweight, perceived birth size , and whether they had a written record of their child's birthweight. If mothers reported a written record of the birthweight, outside of the record provided as part of the trial , the recorded birthweight was captured in line with the approach used in national surveys. These birth record and maternally recalled data serve as our measure of birthweight collected using standard household survey methods and are referred to as “maternally reported” birthweight data throughout the article.We selected mother/child pairs from the parent trial for 1 additional follow-up visit with the aim to interview roughly the same numbers of mothers at each 1, 3, 6, 9, 12, 18, or 24 mo after birth. Mother/child pairs were excluded from this follow-up interview if they were part of a nonsingleton birth. Surveyed pairs were subsequently dropped from the dataset when simulating missing birthweights if In the 2011 Nepal DHS, 67.3% of birthweights were missing for rural households. However, in our substudy, 95.1% of mothers reported a birthweight. Because the objective of our study was to assess the validity of the MINORMIX approach in a typical LMIC survey dataset, we aimed to produce a survey dataset that simulated the missingness commonly observed in national household surveys. We developed an approach to simulate missingness in our trial dataset reflecting the patterns of missingness observed in the 2011 Nepal DHS dataset.Supplemental Table 1 presents the odds of missing birthweight by the 12 a priori selected characteristics of the mother or birth, both individually and adjusting for the other variables. The odds of missing birthweight were associated with birth size, single compared with multiple births, parity, having ≥4 ANC visits, wealth quintile, and maternal education. However, single compared with multiple birth was not included when adjusting the study dataset because this was an exclusion criterion in our substudy.First, we assessed the covariates associated with missing birthweight data in the 2011 Nepal DHS. We hypothesized a priori that missing birthweight in the 2011 Nepal DHS may be associated with whether the mother had ≥4 antenatal care (ANC) visits, birth order of the child, birth size, child sex, singleton/multiple birth, maternal height, maternal BMI, maternal smoking status, birth interval, maternal education, maternal age, and household wealth. We restricted the 2011 Nepal DHS dataset to only households in rural areas to ensure comparability with our study population. We reconstructed the wealth quintile variable to reflect the distribution of wealth in rural households. We then conducted a logistic regression using individual sampling weights to account for differential probability in selection to investigate the association of missing birthweight with the above variables , 18. SupSupplemental Table 2. This dataset with simulated missing birthweights was used for the primary analysis of performance of the LBW adjustment methods.Based on the results of the patterns of missingness in rural households from the 2011 Nepal DHS dataset, we removed birthweights in the trial dataset to simulate the missingness in the Nepal 2011 DHS. We simulated the missingness in our dataset by applying the associations observed in the 2011 Nepal DHS to calculate the predicted probability of each respondent in the trial dataset not reporting a birthweight based on their characteristics and characteristics of the birth. Using computer-generated random numbers and the predicted probability of missingness, ∼63% of maternally reported birthweights were then set to missing. Accounting for the initial 4.9% missing birthweights, we generated a dataset of reported birthweights similar in missingness to the 2011 Nepal DHS. The resulting patterns of birthweight missingness for the 5 associated variables in the simulated dataset compared with the Nepal 2011 DHS are presented in 1) a minimum sample size of ≥200 birthweights available in the dataset, 2) a minimum of ≥30% of births having a birthweight, and 3) no indication of an implausible distribution and/or severe heaping of the birthweights defined as a) ≤55% of all birthweights falling on the 3 most frequent birthweights, b) ≤10% of all birthweights weighing ≥4500 g, and c) ≤5% of births on tail ends of 500 g and 5000 g. We assessed the maternally reported and simulated missing birthweight data quality against the UNICEF/WHO LBW database inclusion criteria to gauge the comparability of the data used in the validation exercise  a crude, unadjusted proportion, and 2) the Blanc–Wardlaw method. We compared the LBW estimates generated using each method with those from our dataset of measured (gold-standard) birthweights.We applied the MINORMIX approach, a 2-component normal mixture model fit to a dataset with multiply imputed missing birthweight, to the maternally reported dataset with simulated missing birthweights to estimate LBW. We also estimated LBW from the maternally reported dataset with simulated missing birthweights using existing methods, including 1) a primary normal distribution that accounts for most birthweights, and 2) a secondary normal distribution that captures the smallest newborns in the left tail of the distribution  and curve fitting (to address heaping) on the accuracy of LBW estimates produced through the MINORMIX method. We compared the estimates of LBW generated using MI alone by calculating LBW with no heaping adjustment following the MI of missing birthweights. We also compared the heaping adjustment alone by fitting 1- and 2-component normal curves to the simulated missing dataset without imputing missing birthweights prior to estimation. All analyses were performed using Stata version 14.0 (StataCorp).n = 3), twin delivery improperly included in the substudy (n = 1), repeat participation due to inclusion of >1 child per mother (n = 11), or missing covariates (n = 14). The final dataset for generating the dataset with simulated missing birthweights included 1499 mother/child pairs. Only 74 (4.9%) children were missing maternally reported birthweights, where the mother reported the child was not weighed (n = 21), was uncertain if the child was weighed (n = 6), or was weighed but could not provide a numerical weight (n = 47). Of the 1499 mothers who were asked if they had a card with a birthweight record, only 22 (1.5%) presented cards provided by a facility. To mimic circumstances of a DHS or MICS data collection, we used birthweights recorded on these facility cards in our dataset of maternally reported birthweights. Of the 1499 pairs included in the simulated missingness analysis, 16 (1.1%) children were missing a gold-standard digital weight measurement within 72 h of birth for reasons including death before measurement (n = 14), parental refusal of weight measurement (n = 1), and missing weight measurement (n = 1). These children were excluded from the comparison of LBW estimation methods.In total, 1528 mothers consented to participate and were interviewed as part of the substudy  of newborns classified as LBW. Supplemental Table 3).We compared the estimates of LBW generated through MI and curve-fitting, independently and jointly  as the most accurate and parsimonious method to adjust LBW estimates derived from household survey data . To valiThe crude LBW estimates currently reported by major household survey programs  are likely biased in that they do not account for missing birthweights, nor do they adjust for birthweight heaping. Using our dataset of reported birthweights simulated to represent patterns of missingness in the 2011 Nepal DHS, the crude LBW estimate of 14.5%  captured barely half the true proportion of LBW based on the gold-standard measured LBW of 27.7% in the same group of births. The crude LBW estimate was similar to those reported in the rural population in the 2011 (12.5%) and 2016 (12.9%) Nepal DHS reports , 20. WitThe previous methods to adjust LBW estimates in the global database , as deveWe explored the relative contribution of both adjusting for missing birthweights and adjusting for heaping through the MINORMIX approach. We found that the MI alone brought the LBW estimate closer to the gold standard. Fitting a normal mixture model alone also yielded an estimate closer to the gold-standard estimate. However, combining MI and fitting a normal mixture model yielded point estimates closest to the real value with good precision, supporting the MINORMIX method employed in the current global database , 16.Wilcox and colleagues described birthweight as having a Gaussian distribution comprised of 2 subpopulations: a “predominant” subpopulation with a Gaussian distribution that encompasses most birthweights, and a “residual” subpopulation made up primarily of LBW newborns , 25. OthOur study used accurate and calibrated scales of research quality to minimize measurement error and produced a similar measured birthweight distribution pattern observed in prior high-quality studies , 24, 26.A much higher proportion of mothers in our study reported a birthweight at follow-up than seen in standard household surveys in Nepal. In the case of home births, mothers likely recalled the birthweight measured during the parent trial because this would have been the only birthweight provided to them. Children delivered in a facility might have been weighed at the facility and during the parent trial participation. In the latter case, we assumed the mother was reporting the weight measurement provided to them during the parent trial. It is not uncommon for a high proportion of birthweights to be missing in large household surveys . We remoAdditionally, considering that most birthweights in our dataset were recalled by mothers rather than transcribed from birth cards, which resulted in strong heaping, our dataset might represent a relatively extreme case of birthweights that would require adjustment. Although strong heaping was evident in the maternally reported birthweight dataset, we removed >60% of birthweights to simulate missingness in the Nepal 2011 DHS. MI was unlikely to impute missing values on multiples of 100 or 500 g, resulting in an approximately two-thirds reduction in indicators of heaping severity compared with the near-complete maternal dataset. As a result, removing heaped birthweights prior to imputation and curve-fitting might have improved the curve fitting approach's performance. Assessment of these methods using other validation datasets would improve our understanding of their performance in populations with different birthweight distributions.In conclusion, LBW estimates in survey reports, and the previous methods employed in the global database to adjust LBW estimates to address heaping and missing birthweights, result in underreporting of LBW. Our validation exercise suggests the new MINORMIX method employed in the current global database developed by the Lancet Low Birthweight Investigator Group produces more accurate LBW estimates. The 2-component normal mixture model with MI method generated LBW estimates more accurate than the Blanc–Wardlaw method when applied to this rural Nepal validation dataset with high LBW prevalence, a large degree of heaped birthweights derived primarily from maternal recall, and a high proportion of missing birthweights. Although the MINORMIX approach was developed using high-quality data from the United States, the method performs significantly better than alternatives when applied as intended to maternally reported birthweight data collected through household surveys in an LMIC. Applying these methods to adjust for biased birthweight estimates can be more complex than the presentation of crude estimates based on those with reported birthweights only. However, given the significant burden of LBW on population health, the consistent production of more accurate LBW estimates for stakeholders warrants the increased complexity. This validation exercise supports the use of the MINORMIX approach to produce more accurate estimates for reporting against the LBW Global Nutrition Target and ensure valid data for global monitoring and response.nxab417_Supplemental_FileClick here for additional data file.


Regarding the controversy about the overdiagnosis of Attention Deficit/Hyperactivity Disorder (ADHD) in children and adolescents there are two main directions addressed as issue of age bias and issue of gender bias. In this relation, replication of findings demonstrating significant overdiagnosis is of importance which make the systematic evaluation of such occurrence necessary.The seminal study by Bruchmüller, Margraf & Schneider, 2012 is replicated here, although in a different cultural context, in this case Iran, as ADHS might be perceived differently there. We assessed both gender bias and the impact of potential overdiagnosis on treatment recommendations.A total of 344 licensed Iranian psychiatrists  participated in this study. Each psychiatrist received a cover letter that introduced the study as well as a case vignette. Overall, there are eight different cases, one child with ADHD and three non-ADHD children, for both a boy (Ali) and a girl (Sara). Participants also received a questionnaire requesting their particular diagnosis, treatment recommendation and the therapist’s sociodemographic information. Chi square tests and multiple logistic regression were applied for data analyses.p < 0.01). With respect to the psychiatrist’s gender, we detected no difference between males or females, as both overdiagnosed ADHD in boys . Furthermore, ADHD overdiagnosis had a direct impact on medication prescription (p < 0.01).Overdiagnosis occurred in both girl and boy children, although overdiagnosis was 2.45 more likely in boys than in girls (This study suggests that diagnosticians should strictly adhere to diagnostic criteria to minimize diagnostic error.The online version contains supplementary material available at 10.1186/s12888-021-03525-3. Attention deficit hyperactivity disorder (ADHD) is one of the most frequently diagnosed disorders of childhood and adolescence, with a pooled worldwide prevalence rate of ~ 5% –3. A metMoreover, accompanied by increasing diagnoses rates of ADHD, there are studies that imply a rise in the rate of psychostimulant prescription. For instance, a longitudinal study by McCarthy et al.  investigWith respect to such diagnosis and prescription rates, on the one hand there are studies suggest that these rates are increased during the past decades due to better recognition in underdiagnosed groups, extended knowledge on psychopathology and diagnostic procedure of the disorder, and increased access to health care in certain groups –10. TherA large body of ADHD research shows that children born close to kindergarten or school cut-off dates, and who are therefore up to a year younger than their classmates, are 30 to 60% more likely to be diagnosed with ADHD –14. In tOverall, the majority of studies report an ADHD gender bias that puts boys at a disadvantage. The rate of boys to girls diagnosed with ADHD is reported to be 3 to 1 in representative population-based studies , and 5 tRegardless of the diverse manifestations of ADHD symptoms in boys and girls, another explanation for the different ratios in boys and girls is clinicians’ subjectivity. Bonati and Reale  state thIn support of this are results from a meta-analysis that estimated the agreement between diagnoses made from clinical evaluations and standardized diagnostic interviews. Overall, such agreement was low to moderate and depended on the disorder, with ADHD resulting in moderate agreement  . HoweverOn the other hand, and in order to defend the validity and reliability of diagnoses and treatment by the professional, it is necessary to work through this debate of overdiagnosis of ADHD in terms of associated socio-economic and individual implications . After aN = 473). Overall, there were significantly more false-positive than false-negative diagnoses confirming the assumption of overdiagnosis, and boys were given significantly more false-positive diagnoses, thus indicating a gender bias to their disadvantage. This gender bias was boosted by the fact that male psychotherapists and psychiatrists were more likely to falsely rate boys positively than their female counterparts. In addition, Bruchmüller, Margraf and Schneider [The application of diagnostic criteria for assessing the false positive and false negative ADHD diagnosis and the specific role of patient gender in therapists’ diagnostic decision making was systemically investigated in a seminal study by Bruchmüller, Margraf and Schneider  in a popchneider  reportedMoreover, overdiagnosis of ADHD in children and adolescents is also investigated in a systematic scoping review (including 344 studies) by Kazda et al. . The resN = 15,124) for the years of 2001 to 2016 reported a prevalence rate of ADHD of 12% (CI 95%: 9.0–15) for children aged six to 14 years in Iran [Aim of the present study was to replicate their study, but based on an Iranian population of psychiatrists. Iran is especially interesting for such a study, as a large survey in 2008 on the multicultural assessment of child and adolescent psychopathology via the Achenbach System of Empirically Based Assessment (ASEBA) and Strength and Difficulties Questionnaire (SDQ) indicated that mean ASEBA and SDQ scores are nearly identical for both genders in large, representative samples speaking 76 languages, except Iran . In this in Iran . Compare in Iran , 4, thatThe current study thus addresses the following questions: 1) Is ADHD overdiagnosed in Iran? 2) Is the gender bias to boys’ disadvantage not confirmed in Iran? 3) Do Iranian psychiatrists reveal a gender bias when diagnosing boys and girls with ADHD? 4) Does ADHD overdiagnosis have an impact on treatment recommendations?ADHD is overdiagnosed in Iran.It is hypothesized that Iranian psychiatrists reveal a gender bias when diagnosing boys and girls with ADHD.It is hypothesized that ADHD overdiagnosis have a direct impact on treatment recommendations.In this relation a priori hypotheses of this study are:Among 367 participants of the study, 23 of them were excluded as essential data (e. g. diagnosis or treatment recommendations) were missing. Therefore, a total of 344 licensed Iranian psychiatrists  considered to be included in this study, among them 165 individuals from Isfahan and 179 individuals from Tehran  and by distributing the case vignettes, including a cover letter and questionnaire (for details on the study procedure see below). In Tehran we used the database of psychiatrists indexed on the Website of the Iranian Psychiatry Association (IPA) and the documents were sent to 300 psychiatrists’ offices. Among the receivers, 179 psychiatrists sent back their ratings via Post, e-mail or telegram. The data collected between 2019 and 2020. All the participants received and signed ethical consents articulated in a session with the committee of the psychiatric association. We assume the overall response rate to be 44.10%  and thus similar to that in the Bruchmüller, Margranf and Schneider study .The cover letter included a brief introduction of this study. In addition, psychiatrists were asked to read a case vignette and answer the questionnaire. We emphasized that despite differences between the fictional case and a real case, they as therapists should treat the case as if it were a real setting.The four case vignettes already used and discussed with respect to their reliability and validity by Bruchmüller, Margraf and Schneider  were alsADHD fulfilled: includes a description of a youth with ADHD who presents all the above-mentioned criteria necessary to diagnose ADHD (combined type) based on ICD-10 and DSM-IV.no ADHD, two criteria missing: The only difference between this one and vignette 1 is that in this case, the youth’s description fails to meet criteria b and c based on DSM-IV and criteria b based on DSM 5. In this regard, the symptoms were apparent in only one setting (school) with the disorder onset after the age of nine years. Therefore, an ADHD diagnosis is not possible relying on either ICD-10 or DSM-IV criteria.no ADHD, three criteria missing: In this case the youth’s description is similar to vignette 2’s, although a third diagnostic criteria was absent. Regarding criterion a, only two hyperactivity/impulsivity symptoms and three inattention symptoms were present. Thus, although this case still contains some aspects of core ADHD features, an ADHD diagnosis is not justified.no ADHD, GAD with symptom overlap: As ADHD symptoms and generalized anxiety disorder (GAD) in childhood/adolescence can overlap, this case was constructed to include restlessness, nervousness, and difficulty concentrating, all of which are manifestations common to both ADHD and GAD. However, these symptoms do not suffice to diagnose ADHD, but rather GAD.As one of the aims of the present study was to test whether the patient’s gender moderates a clinician’s evaluation and diagnosis, the four vignettes were duplicated for boys and girls as in the original study to arrive at 4 vignettes for girls and 4 vignettes for boys. The only difference between the descriptions of boys and girls is that the youth in the girls’ cases is introduced as ‘Sara’, a typical Persian name for girls, and the youth in boys’ cases is called ‘Ali’, a typical Persian name for boys.After duplicating the case vignettes based on the gender there were overall eight vignettes and each psychiatrist randomly received only one of them (between subject design).Attached to the case vignette, all clinicians received a questionnaire that asked for diagnosis, treatment recommendation and their sociodemographic information. In the diagnosis section, psychiatrists were asked to base their diagnosis of the case vignette on DSM-IV criteria, as DSM-IV is the standard diagnostic manual used by mental health experts in Iran.In addition, clinicians were asked whether they would recommend any intervention at all (yes or no), psychotherapy (yes or no) or medical treatment (yes or no).Furthermore, we collected sociodemographic data such as gender, age and years of job experience regarding the therapist’s attributes. We excluded their therapeutic approach as well as the type of therapy training from the original questionnaire as participants were only psychiatrists. In addition, we asked as how helpful they perceived the DSM-IV criteria to be their professional routine , and to estimate their familiarity with the DSM-IV . Moreover, Informed consent was obtained from all individual participants included in the study. Additional informed consent was obtained from all individual participants for whom identifying information is included in this article.The English version of questionnaire and case vignettes are presented in appendix.1 and 2.With respect to the first aim of the current study to determine whether ADHD is overdiagnosed in Iran, the percentage of ADHD diagnosis in all cases was calculated according to Sciutto and Eisenberg . In thisp = 0.132; years of job experience: t = 1.23, df = 342, p = 0.24). Confirming our first hypothesis (overdiagnosis of ADHD) descriptive analysis of all six non-ADHD cases (Vignettes 2–4 with Ali and Sara) showed that 25.2% (n = 65) of therapists diagnosed ADHD among these vignettes, while 51.5% (n = 133) diagnosed another disorder, and 6.6% (n = 17) made no diagnosis at all  required more information to arrive at a diagnosis, and 5.4% (n = 14) asserted a “suspected ADHD”.Psychiatrists’ information on age, gender and years of job experience are summarized in Tables n = 57) of the psychiatrists arrived at an ADHD diagnosis, whereas 5.8% (n = 5) designated another diagnosis. Besides, 34.5% (n = 20) wanted more information to make a diagnosis, and 1.6% (n = 4) suspected a case of ADHD.Regarding ADHD cases (Vignette 1) 66.3% (N = 344) = 14.91, p < 0.01). This suggests that the rate of false-positive diagnosis (ADHD diagnosis in non-ADHD cases) is significantly higher than the rate of false-negative diagnosis (not diagnosing ADHD in ADHD cases), thus implying an overdiagnosis of ADHD. Post hoc comparisons of rates of receiving an ADHD diagnosis by with regard to categories of case vignettes (1–4) revealed that significantly higher rates of ADHD diagnosis were seen among case vignette 1 and 2. In comparison, prevalence of no-ADHD diagnoses or diagnoses other than ADHD, was statistically similar among case vignette 3 and 4.We then compared the rate of false-positive diagnoses (diagnosis of ADHD in non-ADHD cases) to the rate of false-negative diagnoses (diagnosis other than ADHD in ADHD cases). Overall, 65 out of 258 were ADHD diagnoses in non-ADHD cases  and 5 out of 86 were diagnoses other than ADHD in ADHD cases . The odds ratio of overdiagnosis amounted to 5.46. In addition, chi square analysis results confirmed a substantial difference between the non-ADHD and ADHD vignettes  who stated no clear diagnosis due to a lack of information, or asserted a suspected diagnosis. In our primary calculation, we considered those answers as neither false-positive nor false-negative, but correct ones. However, this might affect our results, because it is still unclear what their final decision would have been in those cases. Therefore, in our second analysis, we excluded those answers from our calculations and re-examined our first hypothesis. In this regard, the results still indicating higher false-positive rates than false-negative ones, thus confirming the overdiagnosis of ADHD.As mentioned above, there were psychiatrists in both groups of vignettes  with a probability of 0.83 was the most frequent diagnosis in vignette 4  = 105.31, p < 0.01), the probability of an ADHD diagnosis is calculated better when the predictors are included in the equation. Results of the logistic regression analysis showed that controlling for gender is a significant predictor of ADHD diagnosis. In this relation, in comparison to girls, odds of diagnosing ADHD in boys were more than twice  as high. Furthermore, as Fig. With regard to our second hypothesis, we wanted to explore whether a positive gender bias to the disadvantage of boys is present in Iran or not, as suggested by the Achenbach et al.  study. A2  = 4.86, p < 0.01). The same analysis for boys was also significant  = 10.1, p < 0.01) with an odds ratio of 7.9, based on 29.3 and 5% rates of false-positive and false-negative diagnoses, respectively. These results imply that ADHD is being overdiagnosed in both boy and girl vignettes. However, by comparing the rates of false-positive diagnosis between boy and girl cases, our results demonstrate that boys are given significantly more false-positive diagnoses of ADHD  = 5.87, p < 0.01).Moreover, we examined the overdiagnosis of ADHD separately for boy and girl vignettes. In this relation, the rate of false-positive diagnosis was 20.8% for girl vignettes, while the rate of false-negative ones was 6.5%, resulting in an odds ratio of 3.76 and a significant chi square (X1–4 X psychiatrist’s gender and child’s gender X type of case vignette (ADHD vs non-ADHD). The results of the logistic regression analysis indicated that the therapist’s gender and the interaction variables are not predictive of ADHD diagnosis .With respect to our third study question, namely to identify any gender bias by Iranian psychiatrists in diagnosing boys and girls with ADHD, we separately examined the occurrence of ADHD overdiagnosis by female and male therapists. In addition to the predictor variables, we included two interactions offered by Bruchmüller, Margraf and Schneider , namely 2  = 6.22,p < 0.01; male psychiatrist: X2  = 7.12, p < 0.01). On level two, we repeated the analysis once again by separately examining the occurrence of psychiatrists’ overdiagnosing ADHD in the boy and girl vignettes. Our results indicate that the female psychiatrists’ group rates of false-positive and false-negative diagnosis were 23.8 and 9.1% for girl and 25.4 and 4.8% for boy vignettes, respectively. Our analysis of the chi squares of girl vignettes was not significant  = 2.2,ns, OR = 3.16), while the same statistic was significant for boy vignettes  = 4.17,p < 0.01,OR = 6.8), showing that ADHD is overdiagnosed by female psychiatrists only in boy vignettes. In the male psychiatrists’ group, the rates of false-positive and false-negative diagnosis were 17.7 and 4.2% for girl vignettes, and 33.3 and 5.2% for boy vignettes, respectively. The analysis of chi squares of girl vignettes was not significant  = 2.66,ns, OR = 4.9), while the same statistic was significant for boy vignettes  = 5.89,p < 0.01,OR = 9.0). These results indicate that similar to female psychiatrists, ADHD is overdiagnosed by male psychiatrists only in boy vignettes. On level three, all calculations of previous levels were repeated while we excluded the answers from participants who had stated that either the information was insufficient to arrive at a diagnosis or that they only suspected ADHD. On this level, our results resemble those at previous levels and imply that both male and female psychiatrists are overdiagnosing ADHD, although only in boys.Next, we examined the occurrence of psychiatrists’ overdiagnoses based on their gender on three levels. On level one, calculations were based on the overall case vignettes, i.e., irrelevant of child gender. The rates of false-positive and false-negative diagnoses were 25.8 and 4.65% for male therapists (OR = 7.12) and 24.6 and 6.9% for female therapists (OR = 4.3), respectively. Chi square was significant for both groups, implying that overdiagnosing ADHD is independent of the psychiatrist’s gender  = 4.39,p < 0.01), whereas recommendations for psychotherapy were not significant  = 4.27,p = 0.052). These findings indicate that ADHD overdiagnosis has a direct influence on medication prescriptions. In addition, comparing the treatment recommendations for ADHD cases (vignette 1), our findings show that 43 out of 65 psychiatrists answered the treatment-recommendation question in ADHD cases, and among them, 39 therapists prescribed methylphenidate – making it the most significant prescription for ADHD  = 16.11,p = 0.052). In addition, 15 therapists recommended an adjunctive psychotherapeutic treatment  and 5 therapists prescribed atomoxetine. None of the psychiatrists recommended mere psychotherapy for ADHD children.Addressing our fourth study question, we wanted to examine whether ADHD overdiagnosis reveals an impact on treatment recommendations. For each vignette psychiatrists were asked whether they would recommend any treatment at all and if so, whether they would choose psychotherapy, medication, or both. For vignettes 2–4, chi square tests were calculated to examine differences between treatment recommendations by the psychiatrists who made an ADHD diagnosis and those who did not. Only 172 therapists answered this section in the questionnaire. Our findings show that making an ADHD diagnosis significantly increases treatment recommendations entailing medication (Xn = 29) made no clear diagnosis due to a lack of information, and another 5.4% of psychiatrists (n = 14) asserted a suspected ADHD diagnosis. When including those psychiatrists in our analyses, the calculated rate of false-positive diagnosis and thus rates of overdiagnosis rose further. These results are in line with those of Bruchmüller, Margraf & Schneider [The Regarding our first study question, whether ADHD is overdiagnosed in Iran, we found that 25.2% of the psychiatrists diagnosed ADHD even though ADHD criteria had not been met, and 5.8% of therapists arrived at diagnoses other than ADHD even though the ADHD criteria had been fulfilled. As the false-positive rate of ADHD diagnosis was significantly higher than the false-negative one, our results imply the occurrence of ADHD overdiagnoses among Iranian psychiatrists, thus confirming our first hypothesis. Furthermore, 11.2% of psychiatrists  regardless of whether they are getting any psychotherapy.With respect to potential bias in psychiatrists, post hoc analyses revealed that psychiatrists’ gender, age, years of job experience, as well as the interactions of the child’s gender in case vignette1–4 gender of psychiatrist do not play a significant role in predicting ADHD diagnoses , as mental health disorders are much more prone to subjectivity . Therefore, revision of criteria in DSM-5 does not change our analysis and results.In conclusion, the present study systematically analyzed ADHD overdiagnoses among Iranian psychiatrists; our results reveal that ADHD is being overdiagnosed by both male and female psychiatrists, and that the child’s gender in the vignette also played a significant role, as boys were diagnosed with ADHD twice as often as girls in cases where ADHD should not have been diagnosed. In addition, our findings show that making a false-positive diagnosis of ADHD increases the frequency of psychostimulant treatment recommendations. Overall, our results imply that clinicians should strictly adhere to the criteria offered by ICD or DSM guidelines. In addition, to avoid the overdiagnosis of ADHD, we need to develop strategies to help overcome heuristic biases and reduce diagnostic error.Additional file 1.


Attention‐deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) are generally considered early‐onset disorders so most research has therefore tended to focus on children. Differences between ADHD/ASD in adult life and childhood have been noted, but few population‐based studies have examined them in adulthood. Furthermore, the interpretation of findings is hampered by changes in measure and from parent report to self‐report.N = 6,064). Our aim was to investigate these traits in this population for mean‐level sex differences, overlaps with other cognitive, learning and communication problems and their associations with polygenic risk scores (PRS) for neuropsychiatric disorders .We examined continuous/trait measures of parent‐ and self‐rated ADHD and ASD in adulthood (age 25 years) in a UK prospective longitudinal sample ALPSAC , using many of the same measures that parents reported on in childhood  and ASD (parent‐rated) symptoms showed associations with ADHD PRS; self‐reported ADHD also showed association with depression PRS, whereas self‐reported ASD did not show strong PRS associations.Our findings suggest that in young adults, ADHD and ASD symptoms have similar characteristics as they do in childhood. Associations with other cognitive, learning and communication problems, and ADHD PRS were somewhat less pronounced for self‐reported adult ADHD and ASD symptoms, suggesting that even at age 25, parent reports, where available, could be clinically useful. Attention‐deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) are viewed in DSM‐5 as neurodevelopmental disorders , an index of genetic liability derived from genome‐wide association study (GWAS) data for different psychiatric disorders. Such studies have observed that child ADHD and ASD traits are associated with PRS for ADHD diagnosis , suggesting considerable genetic overlap, although this study could not distinguish childhood‐limited ADHD from ADHD that persisted into adulthood  and examining the pattern of associations with neuropsychiatric PRS . We also explored whether the patterns of association were different when using self‐reports as compared to parent‐reports.We analysed data from the Avon Longitudinal Study of Parents and Children (ALSPAC), a well‐established prospective, longitudinal birth cohort study. Details of this study are provided in Appendix At age 25 years, young adult ADHD symptoms were measured using the parent‐rated 5‐item ADHD subscale of the Strengths and Difficulties Questionnaire (SDQ) Goodman,  range:  range:  for ADHDOur primary measures are continuous, although we also report the proportion of individuals with 'high' symptoms for descriptive purposes. Elevated ADHD symptoms were defined using the childhood/adolescence recommended cut points of ≥8 for the parent‐rated SDQ and ≥7 for the self‐rated SDQ Goodman,  as thereBased on the DSM‐5 conceptualisation of neurodevelopmental disorders  were generated using PRSice version 1.25 . Missing data were addressed by combining imputation with inverse probability weighting , using inverse probability weighting without multiple imputation and using complete cases are also described in Appendix Individuals with parent‐rated or self‐rated ADHD and/or ASD data in young adulthood were included in our analyses ; sensitivity analyses were conducted to investigate associations for each of the five PRS separately. Both unstandardised coefficients (i.e. the ADHD/ASD score increase per one unit change in the exposure variable) and standardised (beta) coefficients (i.e. the ADHD/ASD standard deviation increase per standard deviation change in the exposure variable: generated by standardising variables to mean = 0 and standard deviation = 1) are presented. Sensitivity analyses were conducted stratifying analyses by sex and for persistent/late‐onset ADHD. Late‐onset ADHD was defined using our previous published criterion of symptom onset after age 12 years, based on 4 childhood assessments using the recommended cut points . Parent‐rated (SCDC) and self‐rated (AQ) ASD scores were also associated with male sex .ADHD and ASD mean scores at age 25 years and the proportion of individuals with high symptoms (for descriptive purposes only) are shown in Table r = 0.61, 95% CI = 0.57–0.64, p = 1 × 10−211). Parent‐rated ADHD symptoms in adulthood were moderately correlated with parent‐reported ADHD and ASD symptoms at age 11/12 years , as were adult parent‐rated ASD symptoms .Parent‐rated ADHD and ASD symptoms in young adults were strongly correlated  and with other neurodevelopmental problems , without strong associations with the other neuropsychiatric PRS. This is consistent with previous childhood research   late‐onset ADHD, although differing associations with PRS for different raters could also be driven in part by rater effects in the discovery GWAS patient samples used to derive the PRS. For example, the ADHD and ASD PRS are derived from primarily childhood samples which will rely more heavily on parent ratings, compared with the schizophrenia, depression and anxiety PRS, which are derived from adult samples and therefore are based on interviews, clinical notes and self‐reports, all of which will predominantly reflect patient information rather than parents.When defining categorical outcome measures, we noted that the rate of self‐reported adult ADHD was much higher than when using parent reports, and also higher than reported prevalence rates in epidemiological studies. The mean level of self‐reported (continuous) ADHD symptoms was also higher than parent‐rated symptoms, although the difference was less pronounced than for categorical definitions because the (childhood‐based) symptom cut point for a categorical outcome is lower for self‐reports than parent reports Goodman, . It is iFor ASD, both parent‐ and self‐rated adult ASD symptoms were associated with male sex, lower childhood IQ, reading and spelling scores and language and communication problems. While the magnitudes of the associations were somewhat smaller for self‐ than parent‐rated, this informant difference was less pronounced than was observed for ADHD symptoms – particularly for objective measures . This is despite having different measures for each informant, because our primary aim was to utilise parent reports using the same measures used in childhood and a self‐reported version of the SCDC was not available: we used the self‐rated AQ. Previous work in ASD samples has called into question the validity of the self‐rated AQ, suggesting that for some individuals, self‐report responses may relate to factors other than ASD, such as lack of interest in social interactions , which may have affected their ratings both through increased awareness of these traits and if current ratings were influenced by previous ratings. We were also reliant on repeated measures of ADHD and ASD symptoms that have yet to be validated in adulthood, including what the optimum cut points for defining high symptoms are. Also, the constellation of symptoms for ADHD and ASD may change with age. With regard to the genetic liability associations, PRS currently only explain a small proportion of genetic liability to psychiatric disorders  and sex.Table S2. Univariable associations between neuropsychiatric genetic risk scores and parent‐rated ADHD/ASD symptoms in young adulthood.Table S3. Sensitivity analyses stratifying by sex for parent‐rated ADHD‐ASD symptoms in young adulthood: associations with neurodevelopmental problems and neuropsychiatric genetic risk scores.Table S4. Sensitivity analyses stratifying by sex for self‐rated ADHD‐ASD symptoms in young‐adulthood: associations with neurodevelopmental problems and neuropsychiatric genetic risk scores.Table S5. Sensitivity analyses investigating parent‐rated persistent and late‐onset ADHD symptoms in young‐adulthood: associations with sex, neurodevelopmental problems and neuropsychiatric genetic risk scores.Table S6. Sensitivity analyses investigating self‐rated persistent and late‐onset ADHD symptoms in young‐adulthood: associations with sex, neurodevelopmental problems and neuropsychiatric genetic risk scores.Table S7. Inspecting missingness: Associations between analysis variables and missing young‐adult ADHD/ASD data.Table S8. Associations with parent‐rated ADHD symptoms in young adulthood using different approached to missing data.Table S9. Associations with parent‐rated ASD symptoms in young adulthood using different approached to missing data.Table S10. Associations with self‐rated ADHD symptoms in young adulthood using different approached to missing data.Table S11. Associations with self‐rated ASD symptoms in young adulthood using different approached to missing data.Table S12. Associations between variables include in the inverse probability weight and missing young‐adult ADHD/ASD data.Table S13. Additional measures of ADHD/ASD included in the multiple imputation model: correlations with young‐adult ADHD/ASD measures.Click here for additional data file.