B-cell non-Hodgkin lymphoma (B-NHL) is a lymphoid malignancy derived from B-cells that remains difficult to treat. Moreover, relapses and refractory cases are common. Abnormalities in epigenetic mechanisms, such as imbalanced histone acetylation affecting certain genes, contribute to relapses and refractory cases. Chidamide (tucidinostat) is a novel histone deacetylase inhibitor that can reverse this epigenetic imbalance and has been approved for the treatment of T-cell malignancies. However, the use of chidamide for B-NHL remains limited, and the lack of relevant literature exacerbates this limitation. We conducted this review to summarize the anticancer activity of chidamide against B-NHL and its clinical applications to overcome drug resistance. This systematic review was conducted according to the PRISMA 2020 guidelines, using some keyword combinations from MEDLINE and EBSCO. The inclusion and exclusion criteria were also defined. Of the 131 records retrieved from databases, 16 were included in the review. Nine articles revealed that chidamide limited tumor progression by modifying the tumor microenvironment, stopping the cell cycle, inducing apoptosis and autophagy, and enhancing complement-dependent and antibody-dependent cell-mediated cytotoxicities. According to seven other studies, administering chidamide in combination with another existing therapeutic regimen may benefit not only patients with relapsed/refractory B-NHL but also those with newly diagnosed B-NHL. Chidamide plays many important roles in limiting B-NHL progression through epigenetic modifications. Thus, combining chidamide with other anticancer drugs may be more beneficial for patients with newly diagnosed and relapsed/refractory B-NHL. Non-Hodgkin lymphoma (NHL) is a hematological malignancy of the lymphatic system that shows favorable response to the existing treatments, but some cases remain difficult to treat. Some patients with B-cell NHL (B-NHL) relapse and develop resistance to standard immunochemotherapies . StandarCREBBP), which encodes a histone acetyltransferase, results in a lack of histone acetylation and plays a significant role in lymphomagenesis [CREBBP and EP300 in follicular lymphoma (FL) are associated with disease relapse and poor prognosis [Approximately 90% of NHL is derived from B-cells . A fundaagenesis , 9. For rognosis , 11.Histone deacetylase (HDAC) is an enzyme that deacetylates histones, altering chromatin conformation and preventing transcription. It is comprised of four classes: HDAC Class I ; IIa ; IIb (HDAC6 and 10); III (SIRT1–7); and IV HDAC11). These enzymes are reported to mediate antitumor gene silencing, leading to unfavorable outcomes in patients with B-NHL. Some studies have revealed that HDAC2, 3, and 5 were associated with poor clinical outcomes in DLBCL subtypes [. These e® ). Furthermore, chidamide has been reported to enhance the efficacy of existing standard treatments for certain types of hematological malignancies [Chidamide is a novel HDAC inhibitor (HDACI) that modifies the epigenetic mechanism, inhibits tumor growth by inhibiting HDAC1, 2, 3, and 10 enzymes, and rescues histone acetylation deficits . It was gnancies .There have been no systematic reviews on the role of chidamide in the treatment of B-NHL as a new drug, from its mo lecular mechanism of action to its clinical application. This systematic review updates and summarizes the role of chidamide as an anticancer agent in patients with new and relapsed/refractory (R/R) B-NHL using specific mechanisms. In addition, recommendations and future challenges regarding chidamide utilization are presented.®, we expanded the literature search by including those names in the MEDLINE, EBSCO, and Google Scholar search to obtain the relevant literature. These keywords were used to search for articles published between 2012 and 2022. The inclusion criteria in this analysis were a research article on B-NHL written in English, as determined by the title and abstract of each article, whereas the exclusion criteria were case reports and studies that did not use chidamide. The synthesis was based on preclinical and clinical study articles in which the quality of the included studies had been assessed.A systematic literature search was conducted for all relevant studies according to the updated Preferred Reporting Items for Systematic Reviews Meta-Analysis (PRISMA) guidelines . To idenData were extracted using a standardized form that was approved by all authors. Data extracted from preclinical studies included: (1) authors and year of publication, (2) types of in vitro models used in the experiment, (3) mechanism of action of chidamide for treating B-NHL, and (4) treatment, whereas data extracted from clinical studies included: (1) number of participants, (2) disease diagnosis, (3) median age of participants, (4) interventions, and (5) participant outcomes, including efficacy and safety of each regimen.In this review, the risk of bias in clinical research articles was assessed using the risk of bias in non-randomized studies of interventions (ROBINS-I) assessment tool . All autThe results of the systematic literature search are depicted in The majority of studies on the mechanism of action of chidamide have been conducted using various R/R B-NHL cell lines and tumor xenograft models . The resThe main mechanisms of action of chidamide in the B-NHL are summarized in The clinical outcomes of B-NHL patients evaluated after administration of chidamide included the response rate and overall and progression-free survival, as reported in Many mild to serious adverse events (AEs) have been reported following chidamide-containing regimens administration. Aside from anemia and thrombocytopenia, neutropenia was the most frequent hematological AE, whereas nonhematological AEs included gastrointestinal tract symptoms , infection or sepsis, and fatigue. The majority of AEs in patients who received chidamide-containing regimens were mild.Among six articles, five clinical trial articles and one retrospective cohort article were assessed for risk of bias using ROBIN-I tool . After btable-wrap id="TB3">Table 3

Risk of bias assessment summary using ROBINS-I

<colgroup><col span="1" align="left"/></colgroup>

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BC: Bias due to confounding; BSP: Bias in the selection of participants; COI: Bias in the classification of interventions; BDI: Bias due to deviations from the intended intervention; BMD: Bias due to missing data; BMO: Bias in the measurement of outcomes; BSR: Bias in the selection of the reported result; ROBINS-I: Risk of bias in non-randomized studies of interventions. <italic>Green</italic>: low risk of bias; <italic>yellow</italic>: moderate risk of bias; <italic>red</italic>: serious risk of bias; and <italic>white</italic>: no information.

</table-wrapCREBBP and EP300. Patients with FL who relapsed frequently had a high proportion of mutations in these genes as well [The majority of NHL cases are B-cell subtypes, and DLBCL is the most common subtype of mature B-NHL, accounting for 30%–40% of all new diagnoses , 32. Sev as well . The imp as well .Some pathways involving many proteins can contribute to lymphomagenesis and drug resistance in NHL. Some of these processes appear to be based on epigenetic mechanisms that control intracellular conditions to inhibit apoptosis, stop the cell cycle, increase cell survival and proliferation, and interfere with the optimal functioning of existing therapeutic modalities. The underlying mechanisms by which chidamide limits B-cell lymphoma progression are as follows.Chidamide can stop the cell cycle of B-NHL via several reported mechanisms . The PI3FOXO1 promoter regions. FOXO1 gene expression appears to increase p21/p27 while decreasing cyclin A2, CDK2, and cyclin B1 at both the mRNA and protein levels. Chidamide increases p21 and p27 expressions while decreasing the cell cycle-positive regulators E2F, cyclin, and CDK at both the transcriptional and translational levels, resulting in cell cycle arrest not only in the G0/G1 phase but also in the G2/M phase [Another study found that chidamide (3 µM) could induce cell cycle arrest at the G0/G1 phase in R/R DLBCL and Burkitt lymphoma by altering gene expression profiling. Chidamide promoted gene expression alteration by amplifying histone H3K9 acetylation on /M phase .Chidamide alone could only inhibit HDAC1 and 2 in the SUDHL-4 DLBCL cell line. However, it could inhibit more HDAC enzymes, such as HDAC7 and 10, when combined with venetoclax, a highly selective small-molecule BH3 mimetic with a greater affinity for BCL-2. Inhibiting these enzymes caused an increase in MYC and TP53 mRNA and protein expression. Both were eventually able to activate the CDK inhibitors, allowing B-cell lymphoma to stop the cell cycle in the G0/G1 phase .Some studies reported that some standard treatment modalities failed to induce tumor cell death in B-NHL, resulting in refractory cases. The mechanisms underlying tumor cell failure in programming cell death have been elucidated, suggesting a potential molecular target for chidamide treatment .DLBCL, an aggressive B-NHL subtype, has a high expression of antiapoptotic BCL-2, which can prevent apoptosis in tumor cells. Targeting BCL-2 is expected to overcome therapeutic resistance in B-NHL . The higSTAT3 promoters to modulate its expression [Another proposed mechanism for high STAT3 expression in some kinds of malignancies is nuclear factor kappa B (NF-κB) activity , which cpression . Chidamipression , 58. Thepression .Rituximab, a monoclonal antibody therapy, has been shown to induce apoptosis in B-cell lymphoma. B-cell lymphoma sensitivity to rituximab-induced apoptosis can be augmented by hampering BCL-2 family proteins . InhibitChidamide’s effect on apoptosis was confirmed in vivo, and the results were consistent with in vitro findings. Following chidamide administration, PI3K/PDK1/AKT axis was disrupted, resulting in decreased STAT3 activity and BCL-2 expression and increased apoptosis. A western blot revealed a significant reduction in PDK1 and phospho-AKT expression after chidamide treatment for 36 h, indicating chidamide’s inhibitory activity on the PI3K/AKT pathway. Cancer cell signaling pathways are complex, with the PI3K/AKT pathway and its downstream protein mTOR regulating cell growth and death in many types of cancer , 60. ChiBTG1). Chidamide caused acetyl histone H3K9 to bind to the BTG-1 promoter, suggesting that BTG1 could be a potential chidamide target gene [BTG1 expression, which is caused by acetylated histone H3K9 binding to the BTG1 promoter [Given the presence of many cancer-related features, not all B-NHLs are susceptible to anticancer agent-induced apoptosis. Some of them are resistant to various signaling pathways, preventing apoptosis . Severalget gene . Chidamipromoter . AccordiSurvival of cancer cells depends on the condition of the tumor microenvironment (TME), including immune cells, extracellular matrix, blood vessels, and stromal cells . The TMEThe TME condition changed after administration of chidamide and immune checkpoint inhibitor (ICI)–chidamide combination. Chidamide alone can increase the population of dendritic cells and natural killer cells. In addition, chidamide together with anti-PD-1 can increase the population of other immune cells, such as macrophages and cytotoxic T cells. Bissonnette et al. reported many genes involved in changing TME conditions. Chidamide can increase the work of ICI PD-1 by strengthening gene expression of PD-1, PDL-1, and CTLA-4, thereby significantly reducing tumor volume in in vivo models with both combinations of chidamide and ICI PD-1 .Chidamide with PD-1 antibody augmented the immunosurveillance in TME . Major hGZMB which encodes granzyme B protein and PRF1 which encodes perforin-1 increased significantly on days 7 and 14 after administration of the combination of chidamide and anti-PD-1 [41BB/CD137, tumor necrosis factor alpha (TNFA), interleukin 2 receptor alpha (IL2RA)/CD25, GZMB, IRF4, chemokine (C-X3-X motif) receptor 1 (CXC3R1), chemokine (CXC motif) receptor 6 (CXCR6), and CXCR3 [CXCR6-deficient mice with solid tumor showed poorer control of tumor progression by CD8 T-cells [CXCR6, CXCR3, and other genes by chidamide and ICIs was important for immunisurveillance that limited tumor progression and changed the TME from immunologically nonresponsive to responsive.The effector responses to kill the tumor cells and alteration of TME toward inflammation were enhanced by chidamide and the combination with PD-1 antibody . The gennti-PD-1 . Granzymnti-PD-1 . Subseqund CXCR3 . In anot T-cells . CXCR3 f T-cells . TherefoChidamide could play a synergistic role in upregulating CD20 mRNA and protein expression levels by inhibiting HDAC3. When CD20 proteins are upregulated, rituximab, as a monoclonal CD20 antibody, may act more effectively to promote rituximab-mediated cytotoxicities, such as antibody-dependent cell cytotoxicity and complement-dependentcytotoxicity . The mecTP53, a tumor suppressor gene. MYC needs another genetic events including expression of BCL-2 and mutation in TP53 to induce sustained proliferation and oncogenesis. Therefore BCL-2 overexpression is synergistic with MYC and another oncogene to promote the progression of lymphoma and chemotherapy resistance [Double-expressor lymphoma is defined as DLBCL that displays coexpression of MYC and BCL-2 proteins by immunohistochemistry. This B subtype has a poor prognosis after standard chemoimmunotherapy, high-dose chemotherapy with autologous transplantation, or with allogeneic transplantation . MYC expsistance . Fang etsistance . As prevTP53 expression while increasing BIM expression, a proapoptotic protein. As previously stated, BCL-2 plays an important role in DLBCL apoptosis resistance. Venetoclax is an anticancer agent with a strong affinity for and inhibitory effect on BCL-2 in tumor cell mitochondria. Chidamide and venetoclax can synergistically promote apoptosis by increasing BIM protein expression and reducing BCL-2 family protein activity. However, human clinical trials are required to confirm these promising preclinical findings [Chidamide, an HDACI, can reduce cMYC and findings .Cladribine is an antineoplastic purine analog that can incorporate into DNA, causing single-strand DNA breaks, decreasing nicotinamide adenine dinucleotide and adenosine triphosphate, and promoting apoptosis. It is selectively toxic to lymphocytes due to low deoxynucleotide deaminase activity, which can render antineoplastic drugs inactive . GemcitaLenalidomide is an immunomodulatory agent that is frequently used to treat B-NHL. It can reverse the tumor-supporting network within the local microenvironment in DLBCL, FL, and MCL . Many suMS4A1 gene inactive, which encodes CD20 expression, [Approximately 26% of patients shifted from CD20 positive to CD20 negative after rituximab treatment, as detected by quantitative reverse transcription polymerase chain reaction, immunohistochemistry, and flow cytometry. These findings suggested that some epigenetic mechanisms have a role in decreasing CD20 expression . HDAC3 aression, , 77. Chiression, . Althougression, . Taking Patients receiving rituximab monoclonal antibody therapy benefit from increased CD20 expression. After rituximab administration, lymphoma B-cells become more sensitive to complement-dependent cytotoxicity and antibody-dependent cell cytotoxicity by increasing CD20 expression , 79. comPatients with relapsed and refractory B-cell lymphoma still have a poor prognosis, with long-term survival rates of only 20%–40% . ChimeriChidamide has been reported to increase CD22 expression in lymphoma B-cells. Chidamide, as an HDACI, can regulate post-transcriptional modifications that affect CD22 transport and redistribution, thereby increasing CD22 expression on the cell surface. Yang et al. concluded that chidamide and CD22 CAR-T-cell immunotherapy may enhance CAR-T-cell ability to cure B-NHL with reduced or lost CD22 target antigen .The outcomes of patients with B-NHL who received a drug combination with chidamide were better than those of patients who received chidamide alone. The response of patients with R/R DLBCL who received single chidamide therapy was still low  compared to the combination regimen of chidamide and rituximab (ORR 40%) , 27. ThiCREBBP-proficient DLBCL cells were more resistant to chidamide than CREBBP-deficient DLBCL cells. Because DLBCL patients with CREBBP deficiency showed a more favorable response to chidamide administration, we concluded that CREBBP loss of function that alters epigenetic activity can be used as a biomarker to predict sensitivity to chidamide treatment [CREBBP mutations induce deacetylation by BCL6/SMRT/HDAC3 complexes binding to enhancers of B-cell signaling and immun-response genes. Inhibition of HDAC 3 by chidamide can restore enhancer histone acetylation, allowing the tumor suppressor function of CREBBP in DLBCL to function well. Consistent with the results of a phase II clinical trial, Zhang et al. [CREBBP/EP300-mutant DLBCL. Therefore, we conclude that patients with CREBBP-mutant DLBCL can be well treated with an epigenetic drug that specifically inhibits HDAC3.Not all B-NHL patients are sensitive to chidamide. Some patients are resistant to chidamide and will not receive significant improvement with chidamide. Sun et al. reported that reatment . Jiang ereatment  explaineg et al.  reportedChidamide was found to be more effective for DLBCL treatment when combined with R-CHOP. The response rate of patients with new DLBCL was slightly higher in the chidamide plus R-CHOP (CR-CHOP) group (ORR 94%) than in the R-CHOP alone group ORR 90%). The 2-year overall survival (OS) was also higher in the CR-CHOP group (OS 83%) than in the R-CHOP group (OS 70%) , 89. How%. The 2-The standard treatments for R/R aggressive B-cell lymphoma are high-dose therapy and autologous stem-cell transplantation (HD-ASCT) . The salNot all patients can receive HD-ASCT because of age, comorbidities, and the patient’s unwillingness to receive HD-ASCT . AccordiBased on the mechanism of action revealed in preclinical studies, chidamide has promising antitumor activity. Various chidamide doses  were used in the trials. The patient’s age appears to be a factor in determining the dose. Most of these phase II studies concluded that chidamide combinations showed good results as first-line, second-line, or salvage therapy in patients with B-NHL , 28, 29.The results of the phase II trials on chidamide utilization as advanced therapy for patients with R/R B-NHL show favorable outcomes with tolerable AE in a single or combination therapy. These findings are consistent with previous preclinical studies that demonstrated chidamide’s ability to inhibit B-NHL growth via a variety of mechanisms. The dose of chidamide that can be well tolerated is 30 mg twice a week. A grade III AE (neutropenia) occurred in 14.3% of patients, while no thrombocytopenia and minimal severe nonhematologic AE occurred; none of the patients experienced grade IV treatment-emergent AE after chidamide administration . In contChidamide in combination with other chemotherapy regimens also shows a promising safety profile vs another HDACI. The largest clinical trial examining HDACI vorinostat as combination therapy with the R-CHOP regimen showed grade III–IV hematological AEs as neutropenia (63%), febrile neutropenia (38%), thrombocytopenia, and anemia (36%) in the participants . AdditioNonmutational epigenetic alterations have been identified as a hallmark of cancer, including B-NHL. Chidamide, as an HDACI, has the ability to limit growth, proliferation, and survival of the tumor cells, as well as promote apoptosis and autophagy in B cell lymphoma via various epigenetic and nonepigenetic modifications. Consistent with preclinical studies, chidamide has shown promising results in clinical trials over the last decade as a combination therapy with existing regimens in patients with new and relapse/refractory B-NHL. To recommend chidamide use in patients with B-NHL in daily practice, further clinical trials on a larger population with well-randomized designs are needed.


Is crash risk associated with attention-deficit/hyperactivity disorder (ADHD) in older adult drivers?In this cohort study of 2832 active drivers aged 65 to 79 years, the lifetime prevalence of ADHD was 2.6%. Having ADHD was associated with a 7% increased risk of hard-braking events, a 102% increased risk of self-reported traffic ticket events, and a 74% increased risk of self-reported vehicular crashes.Given this finding that ADHD is associated with a significantly increased crash risk in older adult drivers, improved diagnosis and clinical management of ADHD to promote safe mobility and healthy aging are warranted. This cohort study examines the prevalence of attention-deficit/hyperactivity disorder in older adult drivers and its association with vehicular crash risk. Symptoms of attention-deficit/hyperactivity disorder (ADHD), such as inattentiveness and impulsivity, could affect daily functioning and driving performance throughout the life span. Previous research on ADHD and driving safety is largely limited to adolescents and young adults.To examine the prevalence of ADHD and the association between ADHD and crash risk among older adult drivers.This prospective cohort study collected data from primary care clinics and residential communities in 5 US sites  between July 6, 2015, and March 31, 2019. Participants were active drivers aged 65 to 79 years at baseline enrolled in the Longitudinal Research on Aging Drivers project who were studied for up to 44 months through in-vehicle data recording devices and annual assessments. The data analysis was performed between July 15, 2022, and August 14, 2023.Lifetime ADHD based on an affirmative response to the question of whether the participant had ever had ADHD or had ever been told by a physician or other health professional that he or she had ADHD.g or greater, self-reported traffic ticket events, and self-reported vehicular crashes. Multivariable negative binomial modeling was used to estimate adjusted incidence rate ratios (aIRRs) and 95% CIs of outcomes according to exposure status.The main outcomes were hard-braking events defined as maneuvers with deceleration rates of 0.4Of the 2832 drivers studied, 1500 (53.0%) were women and 1332 (47.0%) were men with a mean (SD) age of 71 (4) years. The lifetime prevalence of ADHD in the study sample was 2.6%. Older adult drivers with ADHD had significantly higher incidence rates of hard-braking events per 1000 miles than those without ADHD , as well as self-reported traffic ticket events per 1 million miles  and self-reported vehicular crashes per 1 million miles . With adjustment for baseline characteristics, ADHD was associated with a significant 7% increased risk of hard-braking events , a 102% increased risk of self-reported traffic ticket events , and a 74% increased risk of self-reported vehicular crashes .As observed in this prospective cohort study, older adult drivers with ADHD may be at a significantly elevated crash risk compared with their counterparts without ADHD. These findings suggest that effective interventions to improve the diagnosis and clinical management of ADHD among older adults are warranted to promote safe mobility and healthy aging. Data from the National Ambulatory Medical Care Survey indicated a 2-fold increase in the diagnosis of ADHD in adults compared with youth from 2008-2009 to 2012-2013.13 For on-road driving outcomes, drivers with ADHD were more prone to receive license suspensions and speeding tickets and to be involved in vehicular crashes.14 A meta-analysis found that having ADHD was associated with an 88% increased risk in self-reported motor vehicle crashes.15 Experimental studies using driving simulators revealed that participants with ADHD had higher average speed, more frequent lane changes, worse vehicle control, a greater likelihood of collisions with an obstacle, and a higher propensity of other adverse driving outcomes than participants without ADHD.17 Risk factors, such as heightened anxiety, could contribute to adverse driving outcomes, such as traffic citations, of individuals with ADHD.18 Moreover, potentially inappropriate medication use is associated with unsafe driving behaviors, as older drivers take more medications than younger drivers.19 However, it remains unclear whether the association of polypharmacy use with crash risk is similar between drivers with and without ADHD.Major symptoms of ADHD may impair cognitive functioning, including complex executive functioning in activities of daily living, such as driving. Previous research showed a positive association between ADHD and unsafe driving behaviors based on self-, informant, and official reports.20 It is well established that older adult drivers have substantially higher fatal crash rates per mile driven than drivers aged 30 to 59 years.21 Despite the aging US driver population and the increasing prevalence of ADHD in adults, research on ADHD and driving safety is limited primarily to adolescents and young adults.18 Few studies have assessed the association of ADHD with crash risk among older adults. In this study, we aimed to examine the prevalence of ADHD and test the hypothesis that ADHD is associated with a significantly increased motor vehicle crash risk in older adult drivers.The proportion of the US licensed driver population accounted for by older adults  increased from 13% in 2011 to 17% in 2020.21 Each site recruited approximately the same number of study participants.21 Driving data, such as hard-braking events and total miles driven, were collected for up to 44 months through an in-vehicle data recording device  installed to an accessible on-board diagnostics II port in the participant’s primary vehicle at the time of enrollment.The Longitudinal Research on Aging Drivers (LongROAD) project was a multisite, prospective cohort study of 2990 active drivers aged 65 to 79 years at baseline. The sample was recruited between July 6, 2015, and March 31, 2017 from primary care clinics or health care systems in 5 sites .21 Older adults with significant cognitive impairment or Alzheimer disease and related dementias were not eligible for enrollment.21 Excluded from this study were 138 participants due to missing data on ADHD status, 19 participants due to missing driving data, and 1 participant due to unreliable data on hard-braking events, yielding 2832 participants for analysis.The eligibility criteria for participating in the LongROAD project were as follows: aged 65 to 79 years at baseline with a valid driver’s license, driving at least once a week on average, residing in the study site catchment area for at least 10 months a year, having no plans to move outside of the catchment area within 5 years, having access to a motor vehicle of the model year 1996 or newer with an accessible on-board diagnostics II port, driving 1 vehicle approximately 80% of the time or more if having access to more than 1 vehicle, being fluent in English, and scoring 4 or higher on the Six-Item Screener.22An annual questionnaire consisting of driving, health, and functioning domains was used to collect self-reported data, such as demographic characteristics, driving performance, and health behaviors. The brown-bag review method was used to collect data on medications and supplements, which were coded according to the pharmacologic and therapeutic classification system established by the American Society of Health-System Pharmacists in the American Hospital Formulary Service Clinical Drug Information.21 While preparing this article, we followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline.Informed consent was obtained from participants, and a certificate of confidentiality was obtained from the National Institutes of Health. The study protocol was approved by the institutional review boards of all involved institutions. The design and methods of the LongROAD project are described in detail elsewhere.Diagnostic and Statistical Manual of Mental Disorders (Fifth Edition).23 Self-reported lifetime diagnoses of depression and anxiety were collected at baseline.The exposure of interest was self-reported lifetime ADHD recorded at baseline. As part of the health and behavior assessment, participants were asked if they have ever had or ever been told by a physician or other health professional that they had “attention-deficit disorder/ADD” or “attention-deficit/hyperactivity disorder/ADHD.” An affirmative answer to the question was coded as having ADHD. Data on attention-deficit disorder and ADHD were combined in this study because attention-deficit disorder is no longer a separate diagnosis according to the g or higher. Secondary outcomes included self-reported traffic violations and crashes collected during the annual follow-up assessment. Data for self-reported traffic ticket events were collected from answers to the question, “How many times in the past year have you received a traffic ticket, other than a parking ticket, where you were found to be guilty, regardless of whether you think you were at fault?” Data for self-reported crashes were collected from answers to the question, “How many accidents have you been involved in over the past year when you were the driver?” All data related to the 3 outcomes of interest were collected during the first 3 years of follow-up . The response rates during the follow-up were 96.6% in the first year, 94.1% in the second year, and 93.9% in the third year.The outcome of primary interest was hard-braking events, which were defined as maneuvers with deceleration rates of 0.424 The other racial and ethnic group included small numbers of Asian, Native and Indigenous American, and Hispanic participants.Demographic and health characteristics were obtained through in-person visits at the study sites. Self-reported data related to age , sex, race and ethnicity , marital status, highest degree or level of education, annual household income in total, and urbanicity  were collected during baseline visits. Self-reported race and ethnicity were recorded because fatality rates from motor vehicle crashes vary considerably across racial and ethnic groups.21 The post hoc powers for detecting the differences at the P = .05 level between drivers with and without ADHD in the incidence rates of hard-braking events, traffic ticket events, and vehicular crashes per mile driven were 100%, 97%, and 96%, respectively. Pearson χ2 tests were used to examine differences in the prevalence of ADHD across covariates. Incidence rates of hard-braking events per 1000 miles driven and self-reported traffic ticket events and vehicular crashes per 1 million miles driven were computed according to baseline demographic characteristics, number of medications the participant was taking, comorbidities (anxiety and depression), and ADHD. Crude IRRs for hard-braking events were computed by dividing the total number of hard-braking events by the total miles driven in each stratum of participant characteristics. Due to overdispersion, multivariable negative binomial modeling was used to estimate adjusted IRRs (aIRRs) and 95% CIs of the 3 outcomes, with miles driven as the offset. A 2-tailed P < .05 was considered statistically significant. For parsimoniousness of the models, only statistically significant covariates were included. All data analyses were performed using SAS OnDemand for Academics, version 3.81 software (SAS Institute Inc).Statistical analysis was performed between July 15, 2022, and August 14, 2023. The sample size of the LongROAD project was estimated to generate adequate person-time of observation for ensuring a study power of more than 80% in detecting a crash incidence rate ratio (IRR) of 3.0 or greater.Of the 2832 older adult drivers included in this study, 1179 (41.6%) were aged 65 to 69 years at baseline, 984 (34.8%) were aged 70 to 74 years, and 669 (23.6%) were aged 75 to 79 years . More than one-half (1500 [53.0%]) of the study participants were women (vs 1332 men [47.0%]), 2423 (85.7%) were non-Hispanic White (vs 211 non-Hispanic Black [7.5%] and 194 other race and ethnicity [6.8%]), 1774 (63.2%) were currently married, 1807 (64.0%) had a bachelor’s or graduate degree, 1988 (72.8%) had an annual household income of $50 000 or greater, 2052 (72.5%) lived in urban areas, and 879 (31.5%) were taking 10 or more medications . The lifP < .001), between those with and without anxiety , and between those with and without depression . The prevalence of ADHD was not significantly associated with age, sex, race and ethnicity, marital status, education, annual household income, and urbanicity.Of the 75 drivers who reported having ADHD at baseline, 57 had attention deficit disorder, 29 had ADHD, and 11 had both, yielding an overall lifetime prevalence of 2.6% . The preThe incidence rates of hard-braking events per 1000 miles were 1.35  for older adult drivers with ADHD and 1.15  for those without ADHD. Significantly increased incidence rates of hard-braking events were also found among those who had anxiety  or depression ; were aged 75 to 79 years , female , non-Hispanic Black , or other race and ethnicity ; were not married ; lived in urban areas ; or were taking 10 or more medications  .The overall incidence rates per 1 million miles of self-reported traffic ticket events and vehicular crashes were 10.04  and 13.83 , respectively. These outcomes varied markedly with baseline demographic and health characteristics . Older a26 Furthermore, we found that ADHD was associated with increased risks of hard-braking events and self-reported traffic ticket events and vehicular crashes among older adult drivers. Extending prior research in adolescent and young adult drivers,19 our findings show that older adults with ADHD may experience an elevated risk of adverse driving outcomes compared with their counterparts without ADHD. Our findings are consistent with previous studies showing that ADHD is associated with an increased risk of vehicular crashes in adolescents and young adults.31The results of this prospective cohort study indicate that the prevalence of ADHD in US older adult drivers between July 2015 and March 2017 was 2.6%, compatible to the prevalence reported in the Netherlands (2.8%) and Sweden (3.3%).31 In alignment with our results, older adults with ADHD did not show statistically significant differences in sex, income, education, or urban residence compared with their counterparts without ADHD.25 Our results are consistent with previous reports that anxiety and depression may be closely linked to ADHD.25 Although the prevalence of ADHD declines with advancing age,32 the increased risk of comorbidities, such as anxiety and depression, could contribute to reduced life expectancy in these individuals. It is noteworthy that the associations between ADHD and all 3 adverse driving safety outcomes remained significant even when adjusting for these associated disorders.Many studies have examined the influences of demographic characteristics and medical conditions on the prevalence of ADHD.14 Older adults with ADHD might have similar issues in evaluating their own driving behaviors due to impaired executive functioning, thus leading to higher driving risks. Drivers with ADHD may have difficulty remaining alert and have a decreased reaction time, resulting in a higher likelihood of collision with obstacles.17 In our study, older adult drivers with ADHD had excess risks of self-reported traffic ticket events and vehicular crashes that were greater than the excess risk of hard-braking events. These differences could be partly due to the limited validity and reliability of hard-braking events as a proxy measure for crashes.36Young adults with ADHD tend to overestimate their driving ability and performance since this disorder can lead to diminished self-assessment and awareness.38 but it is unclear whether reducing polypharmacy use might have beneficial effects on driving performance. Some stimulant pharmacologic medications, such as methylphenidate,40 have been found to improve ADHD symptoms and help alleviate driving errors compared with placebo. A recent study, however, found increased odds of vehicular crashes for individuals treated with stimulants.41 Research supports that although drivers with ADHD who do not take medication may experience more inattention and impatience than drivers with ADHD who take medication, those taking methylphenidate committed a similar number of driving errors as those without ADHD or a history of taking relevant stimulant medications during on-road driving tests.42Our study also showed a threshold effect of the level of polypharmacy on the risk of adverse driving outcomes. Nonstimulant pharmacologic treatments for ADHD, such as atomoxetine, have been shown to be effective in improving symptoms as well as reducing driving errors,10 Challenges of diagnoses include late emergence of obvious symptoms in adulthood and recall bias of childhood-onset symptoms in older adults.43 Late-life cognitive disorders, such as dementia, could obfuscate the diagnosis of ADHD due to shared pathogenic features.44 Meanwhile, the current Diagnostic and Statistical Manual of Mental Disorders (Fifth Edition) criteria45 for ADHD only specify the threshold or the number of applicable symptoms for diagnosis in children, adolescents, and adults, without giving special consideration to older adults. Given its association with driving safety alone, ADHD in older adults merits greater attention.Issues of underdiagnosis and treatment of ADHD in older adults still exist.36 hard-braking events and self-reported traffic ticket events as proxies for unsafe driving behaviors limit the ability to draw causal inferences between ADHD and crash risk. Finally, our results are based on observational data and could be somewhat biased by unmeasured confounders, such as weather and road conditions.This study has several limitations. First, ADHD status was based solely on self-report, which may make the results susceptible to recall bias. Moreover, data on current ADHD symptoms and severity were not available. Second, the LongROAD project participants were not a nationally representative sample since they were disproportionately non-Hispanic White with relatively high levels of educational attainment and household income. Therefore, our findings may not be generalizable to the US older adult driver population. Third, despite being widely used in naturalistic driving studies,The results of this cohort study indicate that the lifetime prevalence of ADHD in older adult drivers was 2.6%. Older adult drivers with ADHD may be at elevated risks of hard-braking events, traffic ticket events, and vehicular crashes. As aging of the driver population continues, effective interventions to improve the diagnosis and clinical management of ADHD among older adults are warranted to promote safe mobility and healthy aging.


Frequency power analysis also indicated that higher delta power in the fronto-central area (p = 6.75e-4) and higher power of theta/beta ratio in the bilateral fronto-temporal area (p = 3.05e-3) were observed in ADHD. By contrast, remarkable subtype differences were found primarily on the visual network (state B), of which ADHD-C have higher occurrence and coverage than ADHD-I , suggesting that children with ADHD-C might exhibit impulsivity of opening their eyes in an eye-closed experiment, leading to hyper-activated visual network. Moreover, the top discriminative features selected from support vector machine model with recursive feature elimination (SVM-RFE) well replicated the above results, which achieved an accuracy of 72.7% and 73.8% separately in classifying ADHD and two subtypes. To conclude, this study highlights EEG microstate dynamics and frequency features may serve as sensitive measurements to detect the subtle differences in ADHD and its subtypes, providing a new window for better diagnosis of ADHD.Attention-deficit/hyperactivity disorder (ADHD) is a prevalent neurodevelopmental disorder in children, usually categorized as three subtypes, predominant inattention (ADHD-I), predominant hyperactivity-impulsivity (ADHD-HI), and a combined subtype (ADHD-C). Yet, common and unique abnormalities of electroencephalogram (EEG) across different subtypes remain poorly understood. Here, we leveraged microstate characteristics and power features to investigate temporal and frequency abnormalities in ADHD and its subtypes using high-density EEG on 161 participants . Four EEG microstates were identified. The coverage of salience network (state C) were decreased in ADHD compared to HC (The online version contains supplementary material available at 10.1007/s00787-022-02068-6. Attention-deficit/hyperactivity disorder (ADHD), characterized by age-inappropriate inattention, hyperactivity and impulsivity, is a common neurodevelopmental disorder in children with an estimated prevalence about 5–6% . It leavElectroencephalogram (EEG) is readily accessible and inexpensive, which measures scalp electrical activity with millisecond temporal resolution produced by neuronal ensembles of the cerebral cortex . It measIn parallel, microstates are global patterns of scalp potential topographies that remain quasi-stable for around 60–120 ms before changing to another quasi-stable map, which is considered to be the cornerstones of the mental states shown in EEG data , 16. StuIn this study, we leverage microstate characteristics and power features to investigate temporal and frequency abnormalities in ADHD and its subtypes using high-density EEG. To achieve these goals, we first calculated four microstate features on ADHD and subtypes, following with group differences comparison for each microstate parameter through a variety of statistical methods. Then independent component analysis (ICA) was conducted on the absolute power of each frequency band to extract coherent electroencephalogram variations within several-related channels across subjects, which were further compared between groups. Finally, a support vector machines model with recursive feature elimination (SVM-RFE) algorithm was adopted to investigate temporal and frequency features with high discriminative power.n = 107) were enrolled from the Peking University Sixth Hospital in Beijing. 54 HCs matched for sex and age were recruited from communities in Beijing. Written informed consent was obtained from all the children and their parents. The study was approved by the Ethics Committee of Peking University Sixth Hospital/Institute of Mental Health. All subjects were interviewed and underwent diagnosis to ADHD using DSM-IV criterion by a qualified psychiatrist. The Kiddie Schedule for Affective Disorders and Schizophrenia for School-Age Children (K-SADS) was used to confirm the diagnosis and subtypes in the ADHD group. Considering the little sample size of hyperactivity subtype, only inattentive subtype  and combined subtype  were included in the present study. All subjects were first diagnosed patients in the clinics and did not receive stable intervention and treatment at present. All the participants met the following criteria: (a) no history of head trauma with a loss of consciousness, neurological illness or other severe disease, and (b) no current diagnosis of schizophrenia, severe emotional disorder, or pervasive developmental disorders and (c) a full-scale IQ above 80. Moreover, as shown in Table p = 0.39) and age  between ADHD and HC. Only marginal group difference was observed in hand (p = 0.04). The ADHD-C subtype also matched well with ADHD-I subtype in gender (p = 0.56), age , and hand (p = 0.98). The severity of symptoms was assessed by ADHD Rating Scale IV, which consists of 18 items matched from the DSM-IV creation, and includes dimensions of inattention score, hyperactivity/impulsivity score and total score [A total of 161 participants, 8–15 years of age, were recruited in the study . The children with ADHD  with Net Station EEG Software. The impedance of all electrodes was kept below 50 kΩ during the data acquisition. All electrodes were physically referenced to Cz (fixed by the EEG acquisition system). The EEG recordings were amplified with a bandpass filter of 0.01–400 Hz  and digitized online at 1000 Hz.https://sccn.ucsd.edu/eeglab/index.php) [Offline EEG processing was conducted using EEGLAB toolbox (dex.php) . Thirty-http://www.thomaskoenig.ch/index.php/software/microstates-in-eeglab/). The current analysis was carried on Matlab R2018b [The microstate analysis was performed using a Matlab plugin for the EEGLAB toolbox  for each frequency band, obtaining seven power matrices. The formed power matrices were analyzed using ICA, which extracts maximally independent components (ICs) through maximization of entropy which measures uncertainty association with a random variable. Each component reflects coherent electroencephalogram variations within several-related channels across groups [t tests, and the corresponding spatial components were converted to Z scores to select top contribution channels. As for comparison between two subtypes, seven power matrices were also similarly constructed on ADHD-C and ADHD-I, followed by ICA decomposition and group difference comparison. The ICA code is available for public use through the EEGIFT Toolbox (https://trendscenter.org/software/eegift) [The aim of this part was to objectively assess and compare the absolute EEG power between different groups. Spectral analysis of absolute power using FFT was carried out for the six frequency bands: delta (1–4 Hz), theta (4–8 Hz), low alpha (8–10 Hz), high alpha (10–12 Hz), beta 12–30 Hz), gamma (30–45 Hz), as well as TBR calculated by the ratio between theta and beta absolute power. The mean power of each frequency band in all channels of all ADHDs and HCs was organized into a  Hz, gamms groups . The dec/eegift) .N input features based on their importance in classification. One or more features having the smallest contribution are eliminated and the kernel matrix is updated using the remaining features. The process is repeated until a predetermined number of features remain [To provide further evidence for the effectiveness of the above significant features, we adopted a SVM with recursive feature elimination (SVM-RFE) algorithm  embeddeds remain . In thisp(A) = 0.99, p(B) = 0.98, p(C) = 0.93, p(D) = 0.99).The four microstates for patients and controls are presented in Fig. F = 8.54, p = 1.56e-5), time of coverage , occurrence , and transition probabilities . Post hoc pairwise group comparisons  and state C (p = 1.46e-3) were markedly decreased in ADHD, while the contribution of state B (p = 2.07e-4) and state D (p = 1.26e-4) were significantly increased in ADHD compared to HC. These results are in keeping with the triple-network model of pathophysiology associated with ADHD [p = 9.85e-7; p = 2.33e-7) was significantly decreased in patients, whereas increased between state B and D  in patients with ADHD compared to HC.Based on the identified microstates, we computed four parameters for each subject: mean duration, time coverage, frequency of occurrence and transition probabilities. Two-way ANOVA analysis showed significant microstate × group interaction effects for mean duration  = 0.99, p(B) = 0.95, p(C) = 0.95, p(D) = 0.99). Two-way ANOVA analysis based on the calculated four microstate parameters demonstrated significant microstate × group interaction effects for mean duration , time of coverage , occurrence , and transition probabilities . Not surprisingly, we found no significant differences in the general properties of microstates C and D between subtypes  was decreased in ADHD-C, whereas increased from state B to state D  in patients with ADHD-C compared to ADHD-I.The four microstates for ADHD-C and ADHD-I are shown in Fig. t tests for each component. The components were selected if they passed Bonferroni correction with 0.05/component numbers and exhibited high activations within the channels. The corresponding spatial maps of the selected components were converted to Z scores to select the top contributing channels with |Z|> 2.As shown in Fig. p = 6.75e-4, passed Bonferroni correction with 0.05/9) and one TBR component  showed significant group differences between ADHD and HC. Since spatial map has been adjusted as HC > ADHD, ADHD-C > ADHD-I on the mean of loading parameters, then the red region indicates higher contribution in HC than ADHD, as well as higher contribution in ADHD-C than ADHD-I. Higher power in ADHD compared to HC was observed in the delta component spanning in the fronto-central area and the TBR component located in the bilateral fronto-temporal area. We did not reveal any significant group differences in other power matrices.Each prepared power matrix was decomposed into 5, 6, 7, 8, 9, 10 components using ICA. Group difference between ADHD and HC were then assessed through two-sample p = 7.65e-3, passed Bonferroni correction with 0.05/6) in ADHD-C compared ADHD-I  both subtypes showed shared aberrant patterns on dynamics of salience (state C) and frontal-parietal network (state D), as well as higher delta power in the fronto-central area and higher TBR power in the fronto-temporal area for ADHD compared to HC. (2) Remarkable subtype microstate differences were found primarily in the visual network (state B) between ADHD-I and ADHD-C as well as higher gamma signals over the posterior occipital region in ADHD-C compared to ADHD-I. (3) The top discriminative features selected from SVM-RFE model well replicated the results identified from group differences, which achieved an accuracy of 72.7% and 73.8% separately in classifying ADHD patients and two subtypes.p = 0.002; p = 0.0015), while the duration and contribution of state D were observably increased  compared to HC. These two states were also highlighted in the subsequent selected features of SVM-RFE model. On the one hand, microstate state C has been attributed to the salience network [Compared to HC, we showed that the occurrence and coverage of state C were decreased in ADHD . In the subsequent SVM-RFE analysis, state B was also revealed as the top discriminative feature between two subtypes. State B has been attributed to the visual network [Besides the shared abnormal patterns in ADHD-C and ADHD-I, the distinct patterns are valuable for understanding the mechanisms of ADHD symptom dimensions. Because the distribution of ADHD subtypes evolves with individual development and functional differentiation, and the mechanisms of their evolution remain unknown , 3. The  network . In a Go network . Consist network , 55. The network , which g network –59. This network , which m network . A task- network . Our fin network , childreOur study has several limitations. First, our sample size was limited, and we only have single site data which containing ADHD and HC, therefore, we cannot replicate the classification study because of the lack of another independent dataset. However, we have tried our best to reduce the over-fitting and improve the stability of the results –66, nameSupplementary file1 (DOCX 629 KB)Below is the link to the electronic supplementary material.


Asthma is the most prevalent respiratory disease caused by chronic airway inflammation. Attention Deficit Hyperactivity Disorder (ADHD) is children's most common psychological and neurodevelopmental disorder. Increased risk for ADHD in patients with inflammatory and autoimmune diseases supports the role of inflammatory mechanisms in the occurrence of ADHD. However, the association between asthma and ADHD remains unclear.This study was designed to evaluate the prevalence of ADHD in patients with asthma who were referred to the clinic of allergy and clinical immunology.This cross-sectional study was conducted on children aged 6 to 18 with asthma at Imam Ali hospital, Karaj, Iran. The patient's demographic data, history of childbirth delivery type, premature birth, hospital admission, family income, birth rate, and family history information related to the patient's asthma and medicines were recorded. ADHD diagnosis was made using the Persian version of Conners Parent Behavioral Problems Rating Scale (CPRS-26).In this study, 677 asthmatic patients were enrolled; 46 patients (6.8%) had ADHD. The probability of ADHD in asthmatic patients inhabited in a rural area, males, and patients with a history of food allergy, allergic rhinitis, urticaria, and eczema was significantly higher (p < 0.05). In addition, our result demonstrated that the likelihood of ADHD in patients with asthma and a history of PICU admission was significantly higher (p < 0.05).The present study showed that severe asthma, was the risk factor for ADHD in patients with asthma. Physicians should be aware of this co-morbidity to refer asthmatic patients who have the symptoms of ADHD to a psychologist. Asthma is one of the most common chronic inflammatory diseases with onset in childhood. The four main asthma symptoms are recurrent cough, wheezing, shortness of breath, and tightness in the chest , 2. It iAttention deficit hyperactivity disorder (ADHD) is the most common behavioral and neurodevelopmental disorder in children, affecting many aspects of a patient's life . ADHD isDetection of increased risk for ADHD in patients with inflammatory and autoimmune diseases, inflammation-associated genes, and studies on markers associated with inflammation support the role of inflammatory mechanisms in the occurrence of ADHD . The eff·5% of individuals with and without ADHD, respectively. The authors included a Swedish population-based cohort study with 1,575,377 individuals, of whom 259,253 (16·5%) had asthma and 57,957 (3·7%) had ADHD. They reported that the prevalence of ADHD was significantly higher in individuals with asthma than those without (p < 0.0001). According to this study, the overall prevalence of ADHD in subjects with and without asthma was 8. 8% and 5.6%, respectively [The prevalence of ADHD in patients with asthma was assessed in a recent meta-analysis. All studies that concerned the association between asthma and ADHD were enrolled. After applying the inclusion and exclusion criteria, 84 out of 2815 articles fulfilled the principles, which included 49 datasets. ADHD was seen in 210,363 participants, contrary to 3,115,168 non-ADHD people. Asthma was found in 16.9% and 11Some case reports of altered behavior and psychosis in children who used ICS  have been reported. It suggested the hypothesis that the link between asthma and ADHD may be because of asthma medication such as inhaled corticosteroids . HoweverADHD disorder has a complicated diagnosis, treatment, and follow-up process, which imposes a great economic and psychological burden on society and the family. It has been proposed that children with asthma could have behavioral diseases such as ADHD more than other children , 15. MosThis cross-sectional study enrolled asthmatic patients aged between 6 and 18 years old. Six hundred seventy-seven unrelated cases with asthma referred to the clinic of allergy and clinical immunology of Imam Ali hospital, Karaj, Iran, were enrolled. The clinical diagnosis of asthma in this study was done by an allergist based on Global Initiative for Asthma (GINA) 2017 criteria, which included a typical history of variable respiratory symptoms such as wheezing, chest tightness, shortness of breath, and coughing. Then, variable expiratory airflow limitation was confirmed by one or more of these tests: positive bronchodilator reversibility test which means increase in Forced expiratory volume in the first second (FEV1) more than 10–12% predicted or positive exercise challenge which means decrease in FEV1 of more than 10–12% predicted or peak expiratory flow (PEF) of more than 15% [Exclusion criteria were as follows: neurodevelopmental delay, epilepsy, cerebral palsy, mental retardation (which was approved by a pediatric neurologist), history of using anti-epileptic drugs.The prevalence of ADHD among asthmatic children is 7%, with a confidence interval of 95% and a maximum acceptable error of 2%; in this study, the sample size of 10% drop in person estimated 685 patients.Demographic and background information of the patients was collected based on a questionnaire designed by the researcher. The hyperactivity-attention deficit status of the patients was evaluated using the Persian version of the Conners Parent Behavioral Problems Rating Scale (CPRS-26). This questionnaire is one of the standard and well-known tools for measuring children's hyperactivity attention deficit, which identifies five factors including learning, psychosomatic, and behavioral problems, as well as impulsivity-hyperactivity, and anxiety. It includes 26 questions, graded according to the severity of symptoms with a Likert scale of completely true = 4, relatively true = 3, somewhat true = 2, and never = 1 .The reliability and validity of this scale have been confirmed in several studies. The reliability and validity of the Persian version of this questionnaire were reported to be 90% and 85%, respectively , 20.Demographic information comprising a comprehensive medical history including age, gender, childbirth delivery type, premature birth, hospital admission, birth rate, atopic dermatitis, allergic rhinitis, food allergy, family income, as well as data concerning patient's asthma including the age of diagnosis, asthma medications and family history of asthma, parent's education, and parent's job were recorded.Information was collected in questionnaire sheets and was analyzed using SPSS statistical software version 25.0 . Qualitative variables were reported as percentage and frequency. Chi-square test was used to analyze the correlation between qualitative variables. Quantities variables analyzed with T-Test or Mann–Whitney (based on parametric or non-parametric).A total of 677 children with asthma  with a median current age of 11.78 ± 2.98 years old were enrolled; among whom 46 patients (6.8%) were diagnosed with ADHD.The mean age of patients with ADHD was 11.02 ± 2.71 years old, whereas the mean age of patients without ADHD was 11.84 ± 2.9 years old . Regarding gender, 34 out of 46 (73.9%) patients with asthma and ADHD were male, whereas, among 631 patients without ADHD, 365 (57.8%) were male. The results showed a significant gender difference in the association between asthma and ADHD . Also, 4.8% of patients with ADHD lived in rural areas, whereas 13% of patients without ADHD lived in rural areas. This indicated that ADHD was significantly related to the place of living . In other words, asthmatic patients who lived in rural areas were significantly more likely to be suffering from concomitant ADHD. There was no significant association between parent’s education with ADHD disease  and ADHD in asthmatic patients. The patients born by a cesarean were divided into three groups based on the reason for cesarean: mother desire, obstetrics indication, and other reasons. Cesarean in patients without ADHD was done in 128 patients for their mother's wish, 95 patients for obstetrics indications, and 117 patients for different reasons. In addition, 12 patients with ADHD were born caesarian because of their mother's desire, six patients for obstetrics indications, and five patients with other reasons. There was a significant difference between the two groups . The duration of asthma symptoms in patients with and without ADHD was 6.73 ± 2.04 years and 7.03 ± 2.02 years, respectively. No considerable distinction was found between patients with and without ADHD regarding the years of suffering from asthma. There was no meaningful correlation between suffering from ADHD and a history of hospitalization because of an asthma attack. The detailed comparison of two study groups regarding demographic data and past medical history are illustrated in Table The mean number of PICU admission was significantly different between the two groups. Patients with ADHD were 2.10 ± 0.99 times admitted to PICU, whereas patients without ADHD were admitted to PICU 1.19 ± 0.60 times .There was no significant difference between the two groups of patients in the type of medicines they received, representing the level of asthma severity and the relationship between ADHD and a specific medication Table .Table 3RThe frequency of attention deficit hyperactivity disorder (ADHD) in children with asthma who were referred to the clinic of allergy and clinical immunology of Imam Ali hospital was evaluated in this study. The study group included 677 patients with asthma; among them, 46 patients (6.8%) had ADHD, which was diagnosed using the Persian version of the Conner’s Adult ADHD Rating Scale questionnaire.This survey showed that the male–female ratio was significantly higher in the group with ADHD than in patients without ADHD. Mu-Hong Chen studied 14,812 atopic subjects, including 9438 (63.7%) with asthma, and in comparison, they studied 6944 non-atopic subjects as a control group. All subjects were followed until the onset of events (ASD or ADHD). They reported that patients with asthma were at a higher risk of ADHD . In addition, the male gender was an independent risk factor for ADHD in asthmatic patients . It mighIn this study, the history of PICU admission due to asthma attack in patients with ADHD was significantly higher than in patients without ADHD. PICU admission indicates the severity of asthma, so it is possible to consider the hypothesis that severe asthma is a risk factor for ADHD. In addition, the average number of hospitalizations in PICU due to asthma attack in patients with ADHD was significantly higher than in patients without ADHD. According to the results obtained about the severity of asthma and ADHD, we suggest that patients with severe asthma could release inflammatory cytokines more than others , 22. TheThere was no considerable correlation between types of medications in the present survey. In line with our findings,  Holmberg et al. reported that asthma medications  didn't increase the risk of ADHD . Also, PIn the present study, the history of allergic rhinitis was significantly higher in patients with ADHD , which concord with the result of the previous studies , 27. Ho Previous studies demonstrated a relationship between ADHD and allergic diseases like asthma, allergic rhinitis, urticaria and eczema, and food allergies, which concord with the present study –32. In aAnyan Huang et al., based on a meta-analysis of 6663 ADHD patients and 93,825 controls published in 2020, suggested that second-hand cigarette smoke exposure may be a risk factor for ADHD. In contrast, this study didn't find any relationship between ADHD and being a second-hand smoker. It might be explained by the higher number of their study population .Aslıhan Yüksel et al. studied children aged 6 to 14, and they evaluated 91 cases with ADHD and 264 without any psychopathology. They reported that tonsillectomy did not predict ADHD, which concurs with this study .In this study, there was no significant relationship between the history of preterm labor in patients with and without ADHD. Whereas, in the previous studies, like a Finnish population-based study on 10,321 ADHD patients and 38,355 controls, a history of preterm labor was found to be a risk factor for ADHD in children [Considering the fact that both ADHD and asthma are amongst the most frequent health problems, the findings of this study, which showed the co-existence of these disorders and evaluated the related risk factors, seem to be worthwhile. This co-morbidity should be taken into account by physicians for timely diagnosis and referring the asthmatic patients who have ADHD symptoms to a psychologist.


Mental restlessness reported by adult with Attention Deficit Hyperactivity Disorder (ADHD) has been mainly explained by excessive mind wandering. However, the description of a mind constantly on the go is also akin to racing thoughts, predominantly described in bipolar disorder. This paper aimed at disentangling mind wandering from racing thoughts in adult with ADHD. Associations between those mental phenomena and the ADHD symptomatology were also investigated.To this aim, 84 adults with ADHD completed self-reported questionnaires, including the Mind Wandering-Deliberate and Mind Wandering-Spontaneous questionnaires, the Racing and Crowded Thoughts Questionnaire and the Daydreaming Frequency Scale. Factorial analysis and multiple linear regressions were performed.The factor analysis yielded a two-factor solution. The first factor encompassed the three facets of racing thoughts and was predicted by emotional lability. The second comprised deliberated-MW, spontaneous-MW and daydreaming, but was neither related to the ADHD symptoms, nor functional impairment.These findings suggest that MW and racing thoughts are two distinguishable mental phenomena. Racing thoughts appear to be a relevant hypothesis to explain the mental restlessness in adult ADHD. ADHD diTo date, the subjective experience of mental restlessness in adults with ADHD is mainly hypothesized to be underpinned by excessive mind wandering (MW)  althoughRacing thoughts are defined as the subjective feeling of rapid and numerous thoughts . Racing Differences can be found between MW and racing thoughts, especially regarding their associations with the ADHD symptomatology. Contrary to deliberate MW, spontaneous MW have been found to be mainly associated with inattention, but also with motor restlessness and impulsivity, in both healthy subjects and adults with ADHD . In ADHDOverall, similarities and dissimilarities can be pointed out between MW and racing thoughts. However, to date, no study has simultaneously explored MW and racing thoughts, raising the question of the overlap between the concepts. On the one hand, considering the similarities, it can be assumed that racing thoughts are equivalent to MW. On the other hand, considering the differences, racing thoughts and MW may be considered as co-occurring mental phenomena contributing to mental restlessness in adult ADHD. To focus on this issue, this study aimed to investigate, simultaneously, self-reported MW and racing thoughts in adult ADHD. To do so, adults with ADHD completed self-report questionnaires measuring MW and racing thoughts in order to specify whether these two concepts are dissociable in ADHD. Moreover, we were interested in the links between thinking peculiarities and ADHD symptomatology and functional impairment. In particular, we expected MW to be predicted by inattention symptoms, whereas hyperactivity and emotional lability should contribute to racing thoughts.2.2.1.M = 32.48 years; SD = 10.23; 57.12% female). Participants were recruited from the outpatient psychiatry clinics of the University Hospital of Strasbourg. ADHD and comorbidities diagnoses were established by senior psychiatrists based on the DSM-5 criteria (The sample included 84 adults with ADHD aged 18–57 (criteria . No excl2.2.The Racing and Crowded Thoughts Questionnaire-13-item (RCTQ-13)  is a 13-The Mind Wandering Deliberate (MW-D) and the Mind Wandering Spontaneous (MW-S) are two 4-item self-reported questionnaires assessing the participants’ propensity to mind wander in daily life, i.e., trait MW . Items aThe Daydreaming frequency scale  is a 12-The Self-Reported Wender-Reimherr Adult Attention Deficit Disorder Scale (SR-WRAADDS)  is a 61-2.3.Descriptive statistics included frequencies and percentages of categorical variables together with means and standard deviations of continuous variables. To test whether racing thoughts and MW are distinct phenomena in adult ADHD, a factor analysis with the principal component extraction method was performed. To simplify and clarify the data, a Varimax rotation with Kaiser normalization was applied. Factors were retained when their eigenvalue was greater than 1. Only non-overlapping items with loadings greater than 0.50 were considered as being part of a factor. Two multiple linear regression analyses were carried out. The first regression analysis was performed to partial out the specific contribution of ADHD symptoms on the extracted factors. The second regression analysis was led to determine the specific contribution of the extracted factor on ADHD functional impairment. These analyses were performed using the factor scores calculated by the software for each extracted component. Analyses were performed using the Jamovi® software (version 2.2.3.0).3.3.1.n = 3) of patients had a current major depression episode, 32.14% (n = 27) had past major depression episode, 15.48% (n = 13) presented a comorbid, but stabilized bipolar disorder, 17.86% (n = 15) presented anxiety disorders and 7.14% (n = 6) were diagnosed with an autism spectrum disorder. 70.24% (n = 59) did not take any psychotropic drugs . Regarding psychiatric comorbidities, 3.57% , the MW-S, the MW-D and the Daydreaming Frequency Scale. The analysis yielded two factors with eigenvalues greater than 1 , explaining 47.47 and 20.29% of the variance. The first factor had strong factor loadings for the three RCTQ-13 subscales. By contrast, the second factor had strong factor loadings for the MW-D, the Daydreaming Frequency Scale and the MW-S see . Given t3.3.Racing/overactive thoughts” and “Mind wandering.”Multiple regression analyses were conducted to partial out the specific contribution of ADHD symptoms on both factors: “Racing/overactive thoughts” factor, the predictors accounted for 20.3% of the variance  and “emotional lability” was the main predictor of scores . Regarding the “Mind wandering” factor, the regression model was not significant . Results of regression analyses were unchanged when comorbidities were entered as covariates in the analysis.The four symptomatic facets of ADHD identified in a recent factor analysis of the SR-WRAADDS  were simultaneously entered as predictors in the model. Results are presented in Racing/overactive thoughts” factor and the “Mind wandering” factor were entered as predictors in the models. Regarding the 4 subscales on ADHD functional impairment of the SR-WRAADDS, the regression models were significant for the “oppositional defiant behaviors,” the “additional symptoms” and the “academic difficulties” subscales .Multiple regression analyses were also conducted to partial out the specific contribution of thought phenomena on functional impairment. The “4.Racing/overactive thoughts” and “Mind wandering.” Accordingly, both factors were found to be associated with distinct ADHD symptoms: emotional lability was the main predictor of the “Racing/overactive thoughts” factor  whereas the other factor comprised the deliberate and spontaneous dimension of MW and the daily MW frequency measure. The two factors were therefore, respectively, labeled “” factor  whereas Racing/overactive thoughts” and “Mind wandering” factors can be explained by the conceptual underpinnings of both thought peculiarities. To date, MW episodes have been characterized according to: (i) their content, indicating whether the thoughts are related or not to the activity at hand (task-[un]related-thoughts)   and (ii)houghts) , 2018. Mhoughts) . This cohoughts) . By conthoughts) . Althoughoughts) . The dynhoughts) . In adulhoughts) , akin tohoughts) , suggestRacing/overactive thoughts” and “Mind wandering” factors is also supported by their respective links with the ADHD symptomatology. Our results showed that emotional lability contributed to the “Racing/overactive thoughts” factor. These findings are consistent with a prior study led by our team, in which elevated cyclothymic temperament traits, reflecting affective lability, and motor hyperactivity were found to be predictive of increased racing thoughts in adults with ADHD . By contrast, the “ of life . However of life , 2016. I of life . Deliber of life  or futur of life . By cont of life , and may of life . Importalability . Indeed,lability , such aslability . As an elability . HoweverWe acknowledge several limitations to this study. First, the questionnaires used to assess MW encompassed only its intentionality dimension. Future studies should aim at comparing racing/overactive thoughts to task-(un)relatedness and especially MW dynamics . Second,In conclusion, this study highlighted for the first time that MW and racing thoughts might correspond to two dissociable thought peculiarities in adults with ADHD, both contributing to the feeling of mental restlessness. Importantly, given the associations between racing thoughts and the ADHD symptoms, but also the relationship between racing thoughts and the functional impairments, racing thoughts should be considered when investigating mental restlessness in adult ADHD.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.This study, involving humans, was approved by Regional ethics committee of the South of France . The study was conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.EM contributed to the study conception, performed the data collection and coding, the statistical analysis, and wrote the first draft of the manuscript. LW, AB, and SW contributed to the study conception, the statistical analysis and the manuscript revision. All authors approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Leveraging a large nationwide study of Icelandic women, we aimed to narrow the evidence gap around female attention-deficit/hyperactivity disorder (ADHD) and cardiometabolic comorbidities by determining the prevalence of obesity, hypertension, type 2 diabetes, and cardiovascular diseases among women with ADHD and examine the association between cardiometabolic conditions and co-occurring ADHD with anxiety and mood disorders, alcoholism/substance use disorder (SUD), self-harm, and suicide attempts.SAGA Cohort Study . To ascertain diagnoses and symptoms, we used self-reported history of ADHD diagnoses, selected cardiometabolic conditions and psychiatric disorders, and measured current depressive, anxiety, and PTSD symptoms through appropriate questionnaires . We calculated age-adjusted prevalences of cardiometabolic conditions by women’s ADHD status and estimated adjusted prevalence ratios (PR) and 95% confidence intervals (CI), using modified Poisson regression models. Similarly, we assessed the association of cardiometabolic conditions and co-occurring ADHD with current psychiatric symptoms and psychiatric disorders, using adjusted PRs and 95% CIs.We conducted a cross-sectional analysis of the nationwide, all-female, population-based We identified 2299 (8.6%) women with a history of ADHD diagnosis. The age-adjusted prevalence of having at least one cardiometabolic condition was higher among women with ADHD (49.5%) than those without (41.7%), , with higher prevalence of all measured cardiometabolic conditions , type 2 diabetes , hypertension , and obesity ). Women with cardiometabolic conditions and co-occurring ADHD had, compared with those without ADHD, substantially increased prevalence of (a) all measured mood and anxiety disorders, e.g., depression , bipolar disorder , posttraumatic stress disorder , social phobia ; (b) moderate/severe depressive, anxiety, and PTSD symptoms with PR = 1.76 (95% CI 1.67–1.85), PR = 1.97 (95% CI 1.82–2.12), and PR = 2.01 (95% CI 1.88–2.15), respectively; (c) alcoholism/SUD, PR = 4.79 (95% CI 3.90–5.89); and (d) self-harm, PR = 1.47 (95% CI 1.29–1.67) and suicide attempts, PR = 2.37 (95% CI 2.05–2.73).ADHD is overrepresented among women with cardiometabolic conditions and contributes substantially to other psychiatric comorbidities among women with cardiometabolic conditions.The online version contains supplementary material available at 10.1186/s12916-023-03160-7. Attention-deficit/hyperactivity disorder (ADHD) is an impairing neurodevelopmental disorder with prevalence of around 3–4% in adults , 2. The cardiometabolic conditions—can lead to a considerable health burden, societal costs, and premature mortality [Although much less studied than mood and anxiety disorders, emerging evidence suggests substantial comorbidity between adult ADHD and chronic conditions such as obesity, type 2 diabetes, hypertension, hyperlipidemia, and cardiovascular diseases , 16–21. ortality , 23. Sysortality –26 have ortality . In thesortality , 25. Furortality , 29. Co-Comorbidity between ADHD and cardiometabolic conditions can be traced to both genetic factors and certain lifestyle-related risk factors, e.g., abnormal eating patterns, physical inactivity, sleep disruption, and high alcohol and nicotine use, all of which are common among adults with ADHD –34. HoweLeveraging a large nationwide study of Icelandic women, we aimed to narrow the evidence gap around female ADHD and cardiometabolic comorbidity by determining the prevalence of obesity, hypertension, type 2 diabetes, and cardiovascular diseases among women with ADHD. To enhance our understanding of mental health among women with cardiometabolic conditions and co-occurring ADHD, we examined associations with anxiety and mood disorders, alcoholism and substance use disorder (SUD), self-harm, and suicide attempts.Stress-And-Gene-Analysis (SAGA) Cohort Study. The SAGA Cohort Study is a prospective cohort study launched in Iceland, in 2018. All women aged 18–69 years, residing in Iceland in March 2018 , were invited to respond to an electronic questionnaire about their history of trauma and physical and mental health. To participate, women had to understand and be capable of responding in Icelandic and have access to electronic identification. In total, 30,403 women consented to participate in the SAGA Cohort study. The distribution of socio-demographic factors of the SAGA cohort participants is comparable with the Icelandic female population [We conducted a cross-sectional analysis of the nationwide, population-based, all-female pulation , 36.ever been diagnosed with attention-deficit/hyperactivity disorder or primarily inattentive ADHD?”).To ascertain women’s ADHD, we used self-reported lifetime history of an ADHD diagnosis , and obesity (BMI ≥ 30) was ascertained based on current self-reported height and weight. We created a composite variable “To ascertain relevant psychiatric disorders, we used self-reported lifetime history of diagnoses of mood and anxiety disorders, and alcoholism or substance use disorders (SUD). In this study, we considered mood disorders , anxiety and stress-related disorders , obsessive–compulsive disorder (OCD), posttraumatic stress disorder (PTSD)), and mental and behavioral disorders due to psychoactive substance ).Patient Health Questionnaire-9 (PHQ-9) [General Anxiety Disorder-7 (GAD-7) [PTSD Checklist for DSM-5 (PCL-5) to assess current symptoms (over the past month) of post-traumatic stress disorder (PTDS) with a cut-off score of 33 [We additionally assessed current symptoms (over the past 2 weeks) of depression with the  (PHQ-9)  and anxi (GAD-7) . To defi (GAD-7) , 38. We re of 33 .World Health Organization (WHO) Composite International Diagnostic Interview (CIDI) [We ascertained lifetime history of self-harm and suicide attempts in all respondents with questions from the w (CIDI) .Demographic characteristics included the following: age , relationship status , number of children , education level , college or equivalent , and postgraduate (MSc or above)), monthly income , conversion rates according to Central Bank of Iceland, February 15, 2023), employment status , disability benefits , smoking status , current other nicotine use , binge drinking  (Table n = 3715) as ascertainment of ADHD and cardiometabolic conditions was not possible without this information  and overall (any cardiometabolic condition) by women’s ADHD diagnosis, using logistic regression models. We assessed associations between ADHD and cardiometabolic conditions by calculating age-adjusted prevalence ratios (PR) and accompanying 95% confidence intervals (CI) separately for each measured cardiometabolic condition and overall, using modified Poisson regression models. We present estimates stratified by women’s age  as additional files  and current symptoms of depression, anxiety, and PTSD, and for lifetime history of self-harm or suicide attempts. We explored the contribution effects of the women’s education level, monthly income, and marital status (SES) on the observed associations by calculating PRs and accompanying 95% CIs for each measured cardiometabolic condition and overall, adjusting for age, education level, monthly income, and marital status.Finally, we examined the number of lifetime psychiatric diagnoses among women with cardiometabolic conditions with and without co-occurring ADHD, by calculating the age-adjusted prevalence of having been diagnosed with one, two, three, four, or five or more, mood, anxiety, and SUD disorders, using stratified multinomial regression models with age as a covariate.We used R (version 4.2.2) for all analyses. The SAGA Cohort Study was approved by the National Bioethics Committee of Iceland (no. VSNb2017110046/03.01) and the Icelandic Data Protection Authority. All participants gave informed consent before participation.Among a total of 26,668 women, 2299 (8.6%) reported having an ADHD diagnosis  and 10,957 (41.1%) reported any cardiometabolic condition . A total of 978 (3.7%) women reported having both ADHD and one or more cardiometabolic condition .Compared with those without ADHD, women with an ADHD diagnosis were younger (36.7 years vs. 44.9 years), more likely to be single (33.6% vs. 23.0%), more likely not to have children (30.3% vs. 18.1%), less likely to have finished higher education, i.e., university and university higher education (35.9% vs. 56.3%), more likely to have low or low-medium income (47.0% vs. 27.9%), and more likely to be inactive from work (retired/disability/sick leave) (23.9% vs. 14.3%)―particularly because of a disability (22.4% vs. 8.8% on disability benefits). They were also more likely to smoke (25.6% vs. 14.3%), use other nicotine (27.6% vs. 12.4%), and binge drink monthly or more often (19.2% vs. 13.2%)  than among those without ADHD 41.7%), yielding an age-adjusted PR of 1.19 (95% CI 1.14–1.25) , hypertension (20.7% vs. 16.3%), type 2 diabetes (4.1% vs. 2.0%), and myocardial infarction (2.1% vs. 0.8%). We observed the highest PRs for history of myocardial infarction  and type 2 diabetes , while the PRs were lower, but still significant, for hypertension  and obesity   compared with those without co-occurring ADHD 32.3%), yielding an age-adjusted PR of 2.04 (95% CI 1.94–2.13). This association was evident for all measured psychiatric disorders, with age-adjusted PRs of 2.38 (95% CI 2.19–2.58) for depression, 4.81 (95% CI 3.65–6.35) for bipolar disorder, 2.96 (95% CI 2.64–3.32) for social phobia, 2.09 (95% CI 1.93–2.27) for GAD, 2.78 (95% CI 2.52–3.07) for PTSD, 4.39 (95% CI 3.52–5.46) for OCD, and 4.79 (95% CI 3.90–5.89) for alcoholism/SUD , yielding age-adjusted PRs of 1.76 (95% CI 1.67–1.85), 1.97 (95% CI 1.82–2.12), and 2.01 (95% CI 1.88–2.15), respectively , self-harm, and suicide attempts generated two main findings. First, cardiometabolic conditions, including obesity, hypertension, type 2 diabetes, and myocardial infarctions, were more prevalent in women with a diagnosis of ADHD than in those without. Second, women with cardiometabolic conditions and co-occurring ADHD had a 2- to 5-fold higher risk of all measured history of psychiatric diagnoses compared with women with cardiometabolic conditions without ADHD.These findings align with emerging evidence showing an association between ADHD and cardiometabolic conditions , 17, 19.Our findings indicate that women with cardiometabolic conditions and co-occurring ADHD have a notably elevated prevalence of poor mental health outcomes, e.g., increased anxiety and depressive symptoms. Poor mental health has been linked to worse outcomes in cardiovascular diseases . The higSAGA Cohort Study is a study on trauma history, it could be that women who had experienced trauma were more likely to participate in the study than women who had not. These women could be more likely to suffer from psychiatric disorders than other women. For example, 8.6% of the women in our study reported a diagnosis of ADHD, which is higher than the reported prevalence of ADHD among female adults in the general population [A strength of this study is a relatively large sample size that is representative of the female adult population in Iceland regarding demographic characteristics. Yet, there are several limitations to be noted. First, this is a cross-sectional study, and we have no information on how or when the psychiatric disorders or cardiometabolic disorders were diagnosed. However, as ADHD typically arises early in development, it precedes the onset of most physical health conditions and mood and anxiety disorders , 47. Secpulation . Third, Our findings highlight the role of ADHD in cardiometabolic conditions and associated psychiatric comorbidities. Our findings indicate that women with ADHD could develop these conditions at an earlier age than other women. Furthermore, women suffering from cardiometabolic conditions and co-occurring ADHD have increased prevalence of both mood and anxiety disorders as well as having a diagnosis of alcoholism or substance use disorder. Moreover, they are at an increased risk of self-harm and suicide attempts. Clinicians, in the field of psychiatry, cardiology, and endocrinology, need to be watchful of the psychiatric and cardiometabolic problems that commonly affect adult women with ADHD to increase their well-being and quality of life and to decrease the risk of early death. These findings also stress the importance of diagnosing women with ADHD early. Treating their symptoms and providing educational and behavioral support could reduce the likelihood of them developing cardiometabolic conditions and psychiatric disorders, by diminishing the impact of lifestyle-related risk factors for cardiometabolic conditions that are often associated with ADHD.Additional file 1: Figure S1. Flowchart of the study sample.Additional file 2: Figure S2. Prevalence and prevalence ratios of any cardiometabolic condition among women with and without ADHD stratified by age. Abbreviations: ADHD, attention-deficit/hyperactivity disorder; CI, confidence interval; CMC, cardiometabolic condition; GAD, generalized anxiety disorder; OCD, obsessive-compulsive disorder; PTSD, posttraumatic stress disorder; SUD, substance-use disorder.Additional file 3: Figure S3. Prevalence and prevalence ratios of cardiometabolic conditions among women with and without ADHD stratified by age. Abbreviations: ADHD, attention-deficit/hyperactivity disorder; CI, confidence interval; CMC, cardiometabolic condition; GAD, generalized anxiety disorder; OCD, obsessive-compulsive disorder; PTSD, posttraumatic stress disorder; SUD, substance-use disorder.Additional file 4: Figure S4. Prevalence and prevalence ratios of psychiatric disorders among women with cardiometabolic conditions and with/without co-occurring ADHD stratified by age. Abbreviations: ADHD, attention-deficit/hyperactivity disorder; CI, confidence interval; CMC, cardiometabolic condition; GAD, generalized anxiety disorder; OCD, obsessive-compulsive disorder; PTSD, posttraumatic stress disorder; SUD, substance-use disorder.