Abstract
Developmental Dyslexia (DD) and Attention-Deficit/Hyperactivity Disorder (ADHD) are neurodevelopmental disorders affecting children’s learning abilities worldwide, but limited research exists in Pakistan. We tried to identify and confirm ADHD and DD in Pakistani school children and their sociodemographic associations. We conducted a case-control study, examining an extensive cohort of children (n = 1260), aged 5 - 19 years from special education program schools, rehabilitation centers, and pediatric clinics between 2022 and 2023. Standardized psychological evaluations were conducted to confirm cases, and clinical, biochemical, demographic, and family history data were collected. About 288 children were identified and diagnosed with ADHD or DD, compared to 27 controls. In our child cohort males dominate the distribution (65%) compared to females (35%) compared to 56% and 44% representation of males and females respectively in controls. Our findings revealed an extensive gender difference within the cases and a significant difference (p-value = 0.05) with Hydroxy D3 levels compared to the control group. Our observations are consistent with previous studies, showing a lack of associations with sociodemographic and blood biochemical levels, suggesting other factors may influence the development of these disorders.
Keywords: Neurodevelopmental Disorder, Dyslexia, ADHD, Biochemical Parameters, Sociodemographic Factors
1. Introduction
Developmental Dyslexia (DD) and Attention-Deficit/Hyperactivity Disorder (ADHD) are neurodevelopmental disorders characterized by distinct and overlapping symptoms that include inattention, hyperactivity, and impulsivity in ADHD, and difficulties in reading and language processing in DD [1]. Both conditions involve genetic, environmental, and neurological factors contributing to their development, and they can persist from childhood into adulthood [2]. Commonly, DD patients exhibit delayed spoken language, letter transposition in words, slow reading, and confusion with direction, poor comprehension, and limited vocabulary [3]. Furthermore, these conditions may also be co-morbid with depressive, bipolar, schizophrenia, and anxiety disorders [4]. Research indicates that individuals can have both disorders concurrently, which can complicate their learning ability and behavioral patterns, impairing their conditions [5]. School-attending children diagnosed with reading disability and hyperactivity demonstrate poor academic attainments and are at an elevated risk of behavioral challenges [6] [7]. Several studies indicate that clinical (biochemical) conditions (e.g., low ferritin and Vitamin D) are associated with such complex neurobehavioral disorders, but this research has not been conclusive [8]-[10]. The worldwide prevalence of DD is 3% to 7%, while ADHD is 5%, and they have a male-to-female ratio of 3:1 [11] [12]. World Health Organization (WHO) data shows that 10% of the global population has a learning disability [7]. Estimates show that 66.3% of diagnosed children and adolescents take medication for the disorder, among whom 4.8% of children are in the age group of 4 - 17 years [6] [13] [14]. In Pakistan, the prevalence of learning disabilities has been estimated from 15% to 20% [15]. This suggests that currently more than 12 million children in Pakistan require special educational programs for these disorders [15] [16].
In the present study, we aimed to identify and confirm ADHD and DD among a broad sample of Pakistani school children. We also explored the associations between these conditions and various risk factors, including gender, family history, and mode of delivery, consanguinity, area of residence, family education, profession, and biochemical and clinical parameters in the affected children, comparing them with a control group.
2. Methods
2.1. Ethical Statement
This study was approved by the Ethical Review Board (ERB) of (CUI), Islamabad, Pakistan (CUI/BIO/ERB/2022/11), on December 19, 2022, and the Howard University Institutional Review Board (IRB-2023-0810) on May 30, 2023, the latter institution approving the transfer of biological specimens to the US for molecular assays. Informed written consents were obtained from the parents or legal guardians prior to enrolment in the study. This research was conducted ethically in accordance with the World Medical Association Declaration of Helsinki.
2.2. Study Design and Participants
Children aged 5 to 19 years were screened from special education program schools including children’s rehabilitation centers (n = 750) and pediatric neuropsychiatric clinics (n = 510) in four major cities: Chakwal, Rawalpindi, Islamabad, and Lahore. For the control group recruitment participants were randomly selected from a regular school in the same area. Initially, a total of 110 children aged between 5 and 19 years were enrolled, and their parents expressed a willingness to participate in the study. However, ultimately, only 27 participants (children) agreed to undergo the psychological evaluation and blood draw. Children with major neurological disorders, impairment in hearing or vision, and those with severe medical conditions were excluded. Medical records were obtained from all recruited participants, including gender, age, residence area, family history, consanguinity, mode of delivery, parents’ education level, and parents’ smoking.
2.3. Psychological Evaluation
To diagnose ADHD and DD, we measured the neuroadaptive profile of each child. It was evaluated by standardized psychological evaluation methods following the criteria of DSM-V [17]. The assessments were conducted in accordance with internationally recognized standard protocols, which included the use of available Urdu-translated questionnaires and tests [15] [18]. Nonverbal assessment was conducted using the Standard Progressive Matrices (SPM) [19]. To evaluate learning ability, problem-solving skills, comprehension, reasoning, judgment, and knowledge retention, the Urdu version of the Slosson intelligence test (SIT R3) was utilized [20] [21]. Reading-writing ability, quantitative knowledge, and cognitive processing speed were measured using the Woodcock-Johnson Tests of Cognitive Abilities (WJ-IV) and the Bangor Dyslexia test [22]-[24]. Additionally, for a comprehensive evaluation of potential behavioral markers of ADHD in children aged 6 - 18 years, the Conners Parent Rating Scale-Long Version (CPRS-R: L) was used. This scale assesses various aspects comprising inattention, hyperactivity/impulsivity, learning problems, executive functioning, and aggression [25] [26].
2.4. Clinical Blood Tests
Clinical biochemistry parameters were retrieved from the participants’ medical records to investigate potential associations. These parameters include blood profile, non-fasting glucose, liver function tests, renal function tests, and Vitamin D3 (VIT-D3) levels. The tests were conducted using the Cobas 6000 Modular System from Roche Diagnostics, Germany, at the Islamabad Diagnostic Laboratory (IDC) in Pakistan.
2.5. Statistical Analysis
We performed two types of statistical analyses to compare cases to controls. Firstly, independent sample t-tests were conducted for continuous variables, including age, serum glucose, WBCs, RBCs, hemoglobin, PVC, MCV, MCH, platelets, polymorph, lymphocytes, Monocytes, serum Bilirubin total, serum ASAT, serum alkaline phosphate, serum creatinine, serum sodium, serum potassium, serum chloride, and Hydroxy vitamin D3 level [27]. Chi-square tests were computed for categorical variables such as gender, pregnancy (mode of delivery), area of residence, family education, family profession, and marriage [28]. All values were presented using percentages or means and standard deviations (±SD). Statistical significance was set at p ≤ 0.05. All statistical analyses were performed using SPSS, version 29.0.
3. Results
3.1. Participant’s Characteristics
Out of a total of 1260 participants, we diagnosed 288 with ADHD and DD (cases) based on scores obtained from our psychological test battery. Based on the psychological evaluation tests, we identified three case subgroups: DD (n = 192), ADHD (n = 20), and DD co-morbid with ADHD (n = 76). A total of 27 children tested normal on all parameters (controls). The average age of the study population (all cases and controls combined) was 13.67 ± 3.03, comprising 187 males (64%) and 101 females (36%) from the case group, and 15 males (56%) and 12 females (44%) in the control group. The mean age in the control and case groups was 11.89 ± 3.67 and 13.84 ± 2.92 years, respectively. In the case group, 20% of participants were aged 6 - 11 years, while 1% were aged 3 - 5 years, with most (71%) falling within the 12 - 17 age range (Table 1). In the case group, 33% were involved in cesarean delivery (C-section), and 72% of families of participants reported consanguineous marriage (marriage within the same family) (Table 1). We observed no differences between cases and controls based on area of residence, family education, and family profession (Table 1).
Table 1.
Participants’ characteristics and socio-demographic status.
| Demographic details | Control n (%) | Cases n (%) | p-value |
|---|---|---|---|
| Gender | 0.33 | ||
| Male | 15 (56) | 187 (65) | |
| Female | 12 (44) | 101 (35) | |
| Age | 0.21 | ||
| 3 - 5 | 0 (0) | 1 (1) | |
| 6 - 11 | 11 (41) | 58 (20) | |
| 12 - 17 | 16 (59) | 204 (71) | |
| 18 or over | 0 (0) | 25 (8) | |
| Age on set | |||
| 3 - 5 | - | 147 (51) | |
| 6 - 11 | - | 141 (49) | |
| Pregnancy (Mode of delivery) | 0.45 | ||
| Other | 20 (74) | 133 (67) | |
| C-Section | 7 (26) | 66 (33) | |
| Area of Residence | 0.20 | ||
| Rural | 0 (0) | 18 (6) | |
| Urban | 27 (100) | 252 (90) | |
| Industrial | 0 (0) | 12 (4) | |
| Family Education | 0.24 | ||
| High School or Below | 12 (45) | 44 (46) | |
| Collage BS/BA | 9 (33) | 41 (43) | |
| MS | 5 (18) | 10 (10) | |
| PHD | 1 (4) | 0 (0) | |
| Professional | 0 (0) | 1 (1) | |
| Family Profession | 0.96 | ||
| Gov/Private Employment | 13 (48) | 47 (49) | |
| Self Employed | 9 (33) | 34 (35) | |
| Farmer | 5 (19) | 16 (16) | |
| Marriage type | 0.59 | ||
| Non consanguineous | 9 (33) | 54 (28) | |
| Consanguineous | 18 (67) | 136 (72) |
3.2. Psychological Evaluation Results
The mean scores of the Standard Progressive Matrices (SPM), Slosson Intelligence Test (SIT R3 adopted Urdu version), and Woodcock-Johnson IV Tests of Achievement (WJ IV Dyslexia), as well as the Bangor Dyslexia Test and Conners Comprehensive-Behavior Rating Scales for DD and ADHD exhibited statistically significant differences from the control group (p values < 0.005), as detailed in Table 2.
Table 2.
Psychological test results.
| Clinical diagnostic details | Control n (%) | Cases n (%) | p-value |
|---|---|---|---|
| SPM in Category | <0.001 | ||
| Intellectually Average | 0 (0) | 56 (19) | |
| Above the average | 26 (96) | 232 (81) | |
| Intellectually Superior | 1 (4) | 0 (0) | |
| Slosson Intelligent | <0.001 | ||
| Borderline | 7 (26) | 238 (83) | |
| Average | 20 (74) | 50 (17) | |
| Bangor Dyslexia | <0.001 | ||
| Normal | 27 (100) | 21 (7) | |
| Moderate | 0 (0) | 191 (67) | |
| Severe | 0 (0) | 76 (26) | |
| Conners Comprehensive Behavior | 0.002 | ||
| Normal | 27 (100) | 189 (66) | |
| Moderate | 0 (0) | 31 (11) | |
| Severe | 0 (0) | 64 (23) | |
| WJ IV Dyslexia | <0.001 | ||
| Low Average | 0 (0) | 266 (92) | |
| Average | 27 (100) | 22 (8) |
3.3. Clinical Blood Test Results
The case group exhibited a marginal difference (p value 0.05) in the mean vitamin D3 level in the case group (20.06 ± 11.97 ng/ml) compared to the control group (31.40 ± 5.01 ng/ml) (Table 3), with cases testing below the normal range of 30 - 100 ng/ml. All additional hematological tests were within normal ranges across the study participants, including Random Glucose level, WBCs, RBCs, Hemoglobin, PVC, MCV, MCH, MCHC, Platelets, Polymorph, Lymphocytes, and Monocytes. Similarly, liver function was within normal ranges, including Serum Bilirubin, Serum ASAT, and Serum alkaline Phosphate. Further renal function tests were also recorded as normal, including Serum creatinine, Serum Sodium, Serum Potassium, and Serum Chloride (Table 3). We did not observe any significant differences in clinical pathology parameters between the control group and any individual disease subgroup (Figure 1 and Figure 2).
Table 3.
Clinical test results.
| Biochemical parameters | Control Average ± SD |
Cases Average ± SD |
p-value |
|---|---|---|---|
| Serum Glucose random (Ref < 160 mg/dL) | 96.04 ± 16.05 | 94.01 ± 13.51 | 0.56 |
| WBCs (Ref 4.0 - 10.0 * 109/L) | 7.44 ± 1.16 | 7.87 ± 1.58 | 0.12 |
| RBCs (Ref 3.8 - 5.8 * 1012/L) | 4.69 ± 0.45 | 4.65 ± 0.51 | 0.75 |
| Hemoglobin (Ref 12 - 14 g/dL) | 12.70 ± 0.70 | 12.44 ± 0.89 | 0.11 |
| PVC (Ref 40% - 50%) | 42.78 ± 2.41 | 43.48 ± 4.91 | 0.30 |
| MCV (Ref 76 - 96 fl) | 85.93 ± 6.03 | 86.09 ± 6.48 | 0.90 |
| MCH (Ref 27 - 31 pg) | 28.59 ± 1.28 | 28.44 ± 2.22 | 0.64 |
| MCHC (Ref 32 - 34 g/dL) | 32.52 ± 0.80 | 32.64 ± 1.76 | 0.60 |
| Platelets (Ref 150 - 400 * 109/L) | 301.30 ± 43.15 | 301.41 ± 53.19 | 0.99 |
| Polymorph (Ref 40% - 75%) | 58.22 ± 8.79 | 58.45 ± 8.71 | 0.90 |
| Lymphocytes (Ref 20% - 45%) | 32.67 ± 7.31 | 34.93 ± 7.84 | 0.17 |
| Monocytes (Ref 01% - 06%) | 3.78 ± 1.58 | 3.73 ± 1.87 | 0.90 |
| Serum Bilirubin total (Ref < 1.3 mg/dL) | 0.84 ± 0.17 | 0.88 ± 0.95 | 0.72 |
| Serum ASAT (Ref < 31 U/L) | 26.00 ± 5.10 | 26.25 ± 3.92 | 0.91 |
| Serum alkaline Phosphate (Ref M/F 100 - 290 U/L, Child: 180 - 615 U/L) | 336.60 ± 47.68 | 329.84 ± 63.23 | 0.77 |
| Serum creatinine (Ref 0.6 - 1.1 mg/dL) | 0.79 ± 0.12 | 1.12 ± 1.60 | 0.065 |
| Serum Sodium (Ref 136 - 149 mmol/L) | 141.80 ± 3.35 | 142.01 ± 5.17 | 0.90 |
| Serum Potassium (Ref 3.2 - 5.2 mmol/L) | 4.09 ± 0.47 | 3.88 ± 0.55 | 0.38 |
| Serum Chloride (Ref 95 - 105 mmol/L) | 98.80 ± 2.77 | 99.44 ± 3.13 | 0.64 |
| Hydroxy vit. D3 Level (Ref: Sufficient 30 - 100 ng/ml) | 31.40 ± 5.01 | 20.06 ± 11.97 | 0.05 |
Figure 1.
Blood biochemical parameters, such as serum glucose random, WBCs, RBCs, hemoglobin, PVC, MCV, MCH, MCHC, and platelet levels, were assessed among the control group, ADHD group, DD group, and the ADHD comorbid with DD group.
Figure 2.
Blood biochemical parameters, such as Polymorph, Lymphocytes, Monocytes, Serum Bilirubin, Serum ASAT, Serum alkaline phosphate, Serum creatinine, Serum sodium, and Serum potassium levels, were assessed among the control group, ADHD group, DD group, and the ADHD co-morbid with DD group.
4. Discussion
DD and ADHD are neurodevelopmental disorders that can co-occur in individuals. Both conditions have distinct characteristics, but they often share some overlapping features [3] [12]. We followed the international standard psychological evaluation batteries to diagnose and differentiate between study groups, including DD, ADHD, DD co-morbid with ADHD, and healthy controls. Dyslexia tests and the Conners Parent Rating Scale-Long Version (CPRS-R: L) for behavioral markers were conducted to differentiate DD and ADHD phenotypes in all study groups. The validity and application of all these tools align with previously conducted studies in the children population [15] [29]. Our psychological assessments provided a comprehensive evaluation of participants’ cognitive and behavioral profiles, revealing significant heterogeneity in their abilities and potential challenges. Notably, a significant number of participants demonstrated above-average performance in nonverbal reasoning and problem-solving skills, indicating a normal range of intellectual ability with strong cognitive capabilities. Despite these strengths, many participants exhibited dyslexic features and ADHD characteristics, as highlighted by the results of the Bangor Dyslexia Test and the Conners Comprehensive Behavior Test (Table 2). The presence of these dyslexic features raises concerns about potential impacts on reading and language processing within this population [30]. Similarly, data obtained from the Conners Comprehensive Behavior Test indicated a high prevalence of ADHD-related symptoms, particularly hyperactivity and impulsivity, among participants. These behavioral characteristics were most pronounced in individuals with co-occurring DD and ADHD. We observed that DD-categorized participants were in the majority, whereas DD co-morbid with ADHD was also high compared to the ADHD group. In overall our observation indicated that despite identifying ADHD or DD categorically through psychological tests, the participating children did not exhibit intellectual impairment. It is important to note that, as per the current psychological testing guidelines, these test scores provide valuable information; however, they should be interpreted in conjunction with other clinical assessments and observations to form a comprehensive understanding of an individual’s cognitive and psychological profile [31]. Other research studies have indicated that children with ADHD tend to exhibit notably lower serum levels of certain vitamins (specifically Vitamin D3, B12, and B6) and higher levels of saturated fatty acids compared to their peers [32] [33]. However, upon reviewing the overall medical records of the affected individuals in our study, no significant changes in their blood biochemical factors were detected, except for a significant insufficiency in vitamin D3 levels. Vitamin D receptors are widely distributed in the neuronal cells of the substantia nigra, hippocampus, hypothalamus, prefrontal cortex, and cingulated gyrus as these regions are significantly well studied in the pathogenesis of ADHD and DD [34] [35]. Furthermore, Vitamin D is essential to produce dopamine and norepinephrine neurotransmitters, which significantly alleviate severe symptoms of ADHD [36]. Our investigation into Vitamin D3 deficiency aligns with previously reported findings from numerous studies [34] [36].
In our study, 65% of male and 35% of female children with DD and ADHD were identified. The proportion of male participants was high, which is consistent with many other studies [37] [38]. Our data suggests a high percentage (70%) of reported cases of DD and ADHD, mostly within the 12- to 17-year age group among the total research participants, which is also consistent with previous findings in other populations [13]. Cases of female children with these disorders are typically much lower than in males, particularly in rural areas of Pakistan, as it is hard to include female participants due to lack of awareness and the social structures, which may account for fewer female subjects in the current study. Specific prenatal and perinatal factors, including low birth weight, prematurity, and mode of delivery (C-sections), play a major contributing role in developmental delay in children [39]. The reported cesarean section rate was high at 32% among the study participants, consistent with other studies. In our cohort, consanguinity rates were approximately 71% while previous studies also revealed that a higher rate of consanguineous marriage is significantly associated with neurodevelopmental disorders in Asian populations [7]. Many studies reported that the presence of a common susceptibility locus (AP4M1 p.E193K) in parents increases the risk of neuro-developmental disorders, including ADHD, schizophrenia, bipolar disorder, autism, and major depressive disorder in their progeny, but we had no data on this locus in our study [9]. Our study provides preliminary insights into ADHD and D) in major cities of Pakistan, highlighting their prevalence and clinical status. Given the lack of awareness, this work aims to address misconceptions and promote early interventions in families, schools, and communities. By contributing to the global database, our study may offer a model for diagnostic practices and socio-demographic analyses in low-resource settings. Future studies should focus on longitudinal studies with more selective cohorts and comparative research on adult populations to explore early-life influences on outcomes and improve risk assessment and therapeutic strategies.
This study had several strengths, including the ability to examine a large case group using standardized psychological batteries alongside clinical and demographic information. However, there were also some limitations. The small sample size of controls may have constrained the statistical significance of case-control comparisons. Furthermore, our study only included four cities in Pakistan, which limits the generalizability of our findings to the broader population.
5. Conclusion
The study identified and confirmed ADHD and DD among Pakistani school children using standard psychological batteries. The study highlighted a substantial gender difference and a lack of significant association with any sociodemographic characteristics and blood biochemical characteristics. Future studies should focus on genetic and molecular factors, to better understand the ADHD and DD conditions and correlates in Pakistani children.
Acknowledgements
We also acknowledge the participation of the children and their families, all collaborative rehabilitation centers and special education schools in the districts of Pakistan incorporated in the study.
Funding
This work was supported by a U54 MD00759731-5859 grant (PI: BS; Project Lead: SG) from the National Institute of Minority Health and Disparity (NIMHD/NIH). This work also received support from Higher Education Commission (HEC), Pakistan1-8/HEC/HRD/2022/12637 (HEC, PAKISTAN) to SH, and CUI Core Grant to MA of COMSTAT University.
Footnotes
Conflicts of Interest
The authors declare no conflicts of interest regarding the publication of this paper.
Data Availability
Data are stored and may be available upon reasonable request complying with the current data sharing policy of NIH, available at https://grants.nih.gov/grants/guide/notice-files/NOT-OD-03-032.html. The data sets used in this study include personal information. Thus, datasets in the RAW format are available from SH and MA of COMSTAT University of Pakistan through the corresponding author, SG, on reasonable requests.
References
- [1].Salari N, Ghasemi H, Abdoli N, Rahmani A, Shiri MH, Hashemian AH, et al. (2023) The Global Prevalence of ADHD in Children and Adolescents: A Systematic Review and Meta-Analysis. Italian Journal of Pediatrics, 49, Article No. 48. 10.1186/s13052-023-01456-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
- [2].Snowling MJ, Hulme C and Nation K (2020) Defining and Understanding Dyslexia: Past, Present and Future. Oxford Review of Education, 46, 501–513. 10.1080/03054985.2020.1765756 [DOI] [PMC free article] [PubMed] [Google Scholar]
- [3].Becker N, Vasconcelos M, Oliveira V, Santos FCD, Bizarro L, Almeida RMMD, et al. (2017) Genetic and Environmental Risk Factors for Developmental Dyslexia in Children: Systematic Review of the Last Decade. Developmental Neuropsychology, 42, 423–445. 10.1080/87565641.2017.1374960 [DOI] [PubMed] [Google Scholar]
- [4].Hendren RL, Haft SL, Black JM, White NC and Hoeft F (2018) Recognizing Psychiatric Comorbidity with Reading Disorders. Frontiers in Psychiatry, 9, Article 101. 10.3389/fpsyt.2018.00101 [DOI] [PMC free article] [PubMed] [Google Scholar]
- [5].Serrallach B, Groß C, Bernhofs V, Engelmann D, Benner J, Gündert N, et al. (2016) Neural Biomarkers for Dyslexia, ADHD, and ADD in the Auditory Cortex of Children. Frontiers in Neuroscience, 10, Article 324. 10.3389/fnins.2016.00324 [DOI] [PMC free article] [PubMed] [Google Scholar]
- [6].Bélanger SA, Andrews D, Gray C and Korczak D (2018) ADHD in Children and Youth: Part 1—Etiology, Diagnosis, and Comorbidity. Paediatrics & Child Health, 23, 447–453. 10.1093/pch/pxy109 [DOI] [PMC free article] [PubMed] [Google Scholar]
- [7].Cortese S, Song M, Farhat LC, Yon DK, Lee SW, Kim MS, et al. (2023) Incidence, Prevalence, and Global Burden of ADHD from 1990 to 2019 across 204 Countries: Data, with Critical Re-Analysis, from the Global Burden of Disease Study. Molecular Psychiatry, 28, 4823–4830. 10.1038/s41380-023-02228-3 [DOI] [PubMed] [Google Scholar]
- [8].Hasan CM, Islam M, Mahib MR and Arju MC (2016) Prevalence and Assessment of Biochemical Parameters of Attention-Deficit Hyperactivity Disorder Children in Bangladesh. Journal of Basic and Clinical Pharmacy, 7, 70–74. 10.4103/0976-0105.183261 [DOI] [PMC free article] [PubMed] [Google Scholar]
- [9].Becker N, Vasconcelos M, Oliveira V, Santos FCD, Bizarro L, Almeida RMMD, et al. (2017) Genetic and Environmental Risk Factors for Developmental Dyslexia in Children: Systematic Review of the Last Decade. Developmental Neuropsychology, 42, 423–445. 10.1080/87565641.2017.1374960 [DOI] [PubMed] [Google Scholar]
- [10].Juneja M, Jain R, Singh V and Mallika V (2010) Iron Deficiency in Indian Children with Attention Deficit Hyperactivity Disorder. Indian Pediatrics, 47, 955–958. 10.1007/s13312-010-0160-9 [DOI] [PubMed] [Google Scholar]
- [11].Chung W, Jiang S, Paksarian D, Nikolaidis A, Castellanos FX, Merikangas KR, et al. (2019) Trends in the Prevalence and Incidence of Attention-Deficit/Hyperactivity Disorder among Adults and Children of Different Racial and Ethnic Groups. JAMA Network Open, 2, e1914344. 10.1001/jamanetworkopen.2019.14344 [DOI] [PMC free article] [PubMed] [Google Scholar]
- [12].Wagner RK, Zirps FA, Edwards AA, Wood SG, Joyner RE, Becker BJ, et al. (2020) The Prevalence of Dyslexia: A New Approach to Its Estimation. Journal of Learning Disabilities, 53, 354–365. 10.1177/0022219420920377 [DOI] [PMC free article] [PubMed] [Google Scholar]
- [13].Slobodin O and Davidovitch M (2019) Gender Differences in Objective and Subjective Measures of ADHD among Clinic-Referred Children. Frontiers in Human Neuroscience, 13, Article 441. 10.3389/fnhum.2019.00441 [DOI] [PMC free article] [PubMed] [Google Scholar]
- [14].Suzuki T, Wada K, Nakazato M, Ohtani T, Yamazaki M and Ikeda S (2023) Associations between Adult Attention-Deficit/Hyperactivity Disorder (ADHD) Traits and Sociodemographic Characteristics in Japanese Workers. Neuropsychiatric Disease and Treatment, 19, 759–773. 10.2147/ndt.s398478 [DOI] [PMC free article] [PubMed] [Google Scholar]
- [15].Ashraf F and Najam N (2020) An Epidemiological Study of Prevalence and Comorbidity of Non-Clinical Dyslexia, Dysgraphia and Dyscalculia Symptoms in Public and Private Schools of Pakistan. Pakistan Journal of Medical Sciences, 36, 1659–1663. 10.12669/pjms.36.7.2486 [DOI] [PMC free article] [PubMed] [Google Scholar]
- [16].Khalid M and Anjum G (2019) Use of Remedial Teaching Approaches for Dyslexic Students: Experiences of Remedial Teachers Working in Urban Pakistan. Cogent Psychology, 6, Article ID: 1580181. 10.1080/23311908.2019.1580181 [DOI] [Google Scholar]
- [17].American Psychiatric Association (2013) Diagnostic and Statistical Manual of Mental Disorders: DSM-5. American Psychiatric Association. [Google Scholar]
- [18].Ashraf M and Majeed S (2011) Prevalence of Dyslexia in Secondary School. Pakistan Journal of Psychological Research, 26, 73–85. https://pjpr.scione.com/cms/abstract.php?id=336 [Google Scholar]
- [19].John, and Raven J (2003) Raven Progressive Matrices. In: McCallum RS Ed., Handbook of Nonverbal Assessment, Springer, 223–237. 10.1007/978-1-4615-0153-4_11 [DOI] [Google Scholar]
- [20].Jaffar R and Ali AZ (2021) Using Urdu-English Code-Switching in the Translation of Slosson Intelligence Test. Pakistan Journal of Educational Research, 4, 389–401. [Google Scholar]
- [21].Slosson RL, Nicholson CL and Hibpshman TH (1991) Slosson Intelligence Test Revised (SIT-R3). Slosson Education Publications. [Google Scholar]
- [22].Miles TR, Wheeler TJ and Haslum MN (2003) The Existence of Dyslexia without Severe Literacy Problems. Annals of Dyslexia, 53, 340–354. 10.1007/s11881-003-0016-2 [DOI] [Google Scholar]
- [23].Reynolds MR and Niileksela CR (2015) Test Review: Schrank FA, Mcgrew KS, & Mather N, (2014). Woodcock-Johnson IV Tests of Cognitive Abilities. Journal of Psychoeducational Assessment, 33, 381–390. 10.1177/0734282915571408 [DOI] [Google Scholar]
- [24].Schrank FA and Wendling BJ (2018) The Woodcock-Johnson IV. In: Flanagan DP, McDonough EM and Kaufman AS, Eds., Contemporary Intellectual Assessment: Theories, Tests, and Issues, The Guilford Press, 383. [Google Scholar]
- [25].Conners CK (1998) Rating Scales in Attention-Deficit/Hyperactivity Disorder: Use in Assessment and Treatment Monitoring. Journal of Clinical Psychiatry, 59, 24–30. [PubMed] [Google Scholar]
- [26].Conners CK, Sitarenios G, Parker JDA and Epstein JN (1998) The Revised Conners' Parent Rating Scale (CPRS-R): Factor Structure, Reliability, and Criterion Validity. Journal of Abnormal Child Psychology, 26, 257–268. 10.1023/a:1022602400621 [DOI] [PubMed] [Google Scholar]
- [27].Mondal T, Loffredo CA, Simhadri J, Nunlee-Bland G, Korba B, Johnson J, et al. (2022) Insights on the Pathogenesis of Type 2 Diabetes as Revealed by Signature Genomic Classifiers in an African American Population in the Washington, DC Area. Diabetes/Metabolism Research and Reviews, 39, e3589. 10.1002/dmrr.3589 [DOI] [PubMed] [Google Scholar]
- [28].Simhadri JJ, Loffredo CA, Mondal T, Noreen Z, Nnanabu T, Quartey R, et al. (2022) Correlates and Covariates of Type 2 Diabetes in an African American Population in the Washington DC Area. Open Journal of Epidemiology, 12, 431–448. 10.4236/ojepi.2022.124035 [DOI] [PMC free article] [PubMed] [Google Scholar]
- [29].Zahra J, Jamil F and Khalid R (2014) Development and Preliminary Validation of an Indigenous Scale for Assessment of Learning Disabilities. Pakistan Journal of Social and Clinical Psychology, 12, 27–37. [Google Scholar]
- [30].Marchand-Krynski M, Bélanger A, Morin-Moncet O, Beauchamp MH and Leonard G (2018) Cognitive Predictors of Sequential Motor Impairments in Children with Dyslexia and/or Attention Deficit/Hyperactivity Disorder. Developmental Neuropsychology, 43, 430–453. 10.1080/87565641.2018.1467421 [DOI] [PubMed] [Google Scholar]
- [31].Committee on Psychological Testing, Including Validity Testing, for Social Security Administration Disability Determinations, Board on the Health of Select Populations and Institute of Medicine (2015) Psychological Testing in the Service of Disability Determination, Washington (DC). National Academies Press. https://www.ncbi.nlm.nih.gov/books/NBK305236 [Google Scholar]
- [32].Wang L, Yu Y, Fu M, Yeh W, Hsu J, Yang Y, et al. (2019) Dietary Profiles, Nutritional Biochemistry Status, and Attention-Deficit/Hyperactivity Disorder: Path Analysis for a Case-Control Study. Journal of Clinical Medicine, 8, Article 709. 10.3390/jcm8050709 [DOI] [PMC free article] [PubMed] [Google Scholar]
- [33].Sharif MR, Madani M, Tabatabaei F and Tabatabaee Z (2015) The Relationship between Serum Vitamin D Level and Attention Deficit Hyperactivity Disorder. Iranian Journal of Child Neurology, 9, 48–53. [PMC free article] [PubMed] [Google Scholar]
- [34].Chong JX, Buckingham KJ, Jhangiani SN, Boehm C, Sobreira N, Smith JD, et al. (2015) The Genetic Basis of Mendelian Phenotypes: Discoveries, Challenges, and Opportunities. The American Journal of Human Genetics, 97, 199–215. 10.1016/j.ajhg.2015.06.009 [DOI] [PMC free article] [PubMed] [Google Scholar]
- [35].Herken H, Kabukçu Başay B, Büber A, Başay Ö, Alacam H, Öztürk Ö, et al. (2016) White Matter Alterations Related to Attention-Deficit Hyperactivity Disorder and COMT val158 Met Polymorphism: Children with Valine Homozygote Attention-Deficit Hyperactivity Disorder Have Altered White Matter Connectivity in the Right Cingulum (Cingulate Gyrus). Neuropsychiatric Disease and Treatment, 12, 969–981. 10.2147/ndt.s104450 [DOI] [PMC free article] [PubMed] [Google Scholar]
- [36].Rabbani B, Tekin M and Mahdieh N (2013) The Promise of Whole-Exome Sequencing in Medical Genetics. Journal of Human Genetics, 59, 5–15. 10.1038/jhg.2013.114 [DOI] [PubMed] [Google Scholar]
- [37].De Rossi P, Pretelli I, Menghini D, D’Aiello B, Di Vara S and Vicari S (2022) Gender-Related Clinical Characteristics in Children and Adolescents with ADHD. Journal of Clinical Medicine, 11, Article 385. 10.3390/jcm11020385 [DOI] [PMC free article] [PubMed] [Google Scholar]
- [38].Faheem M, Akram W, Akram H, Khan MA, Siddiqui FA and Majeed I (2022) Gender-Based Differences in Prevalence and Effects of ADHD in Adults: A Systematic Review. Asian Journal of Psychiatry, 75, Article ID: 103205. 10.1016/j.ajp.2022.103205 [DOI] [PubMed] [Google Scholar]
- [39].Xu M, Yu X, Fan B, Li G and Ji X (2023) Influence of Mode of Delivery on Children’s Attention Deficit Hyperactivity Disorder and Childhood Intelligence. Psychiatry Investigation, 20, 714–720. 10.30773/pi.2022.0310 [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
Data are stored and may be available upon reasonable request complying with the current data sharing policy of NIH, available at https://grants.nih.gov/grants/guide/notice-files/NOT-OD-03-032.html. The data sets used in this study include personal information. Thus, datasets in the RAW format are available from SH and MA of COMSTAT University of Pakistan through the corresponding author, SG, on reasonable requests.