|Year : 2019 | Volume
| Issue : 9 | Page : 1241-1251
Pattern of attention deficit hyperactivity disorder among primary school children in Ile-Ife, South-West, Nigeria
OJ Oke, SB Oseni, EA Adejuyigbe, SK Mosaku
Department of Paediatrics, Obafemi Awolowo University Ile-Ife, Ile-Ife, Osun, Nigeria
|Date of Acceptance||27-May-2019|
|Date of Web Publication||6-Sep-2019|
Dr. O J Oke
Department of Paediatrics and Child Health, Obafemi Awolowo University Ile-Ife, Ile-Ife, Osun
Source of Support: None, Conflict of Interest: None
| Abstract|| |
Background: One of the most common neurodevelopmental problems affecting behavior of children all over the world is attention deficit hyperactivity disorder (ADHD). Studies on ADHD prevalence in Africa used either parents' or teachers' disruptive behavioral disorder rating scale (DBDRS) to diagnose ADHD, but this study diagnose ADHD using both parents and teachers DBDRS simultaneously among primary school pupils in Ile-Ife. Materials and Methods: The study was conducted among 1,385 primary school pupils in Ile-Ife using multistage random sampling. The parents' and teachers' DBDRS were used simultaneously to screen children who had ADHD. Results: Sixty-five (4.7%) of the pupils had ADHD. Among the 65 pupils with ADHD, 28 (43%) had the inattentive subtype, 25 (38.5%) had the combined subtype, whereas 12 (18.5%) had hyperactive/impulsive subtype. The prevalence of ADHD was significantly higher in the younger age group than the older age groups (χ2 = 7.153, P = 0.007). There was no significant association found between the prevalence of ADHD and the social class (χ2 = 3.852, P = 0.146). Conclusion: ADHD prevalence of 4.7% was found among the children in Ile-Ife. Assessment of children for ADHD was done by parents at home and teachers in the school with DBDRS. The inattentive subtype was the most common and the hyperactive subtype was the least seen in the study. Early diagnosis and treatment of this disorder will bring better outcome in the children.
Keywords: Attention deficit hyperactivity disorder, disruptive behavioral disorder rating scale, Nigeria, school children
|How to cite this article:|
Oke O J, Oseni S B, Adejuyigbe E A, Mosaku S K. Pattern of attention deficit hyperactivity disorder among primary school children in Ile-Ife, South-West, Nigeria. Niger J Clin Pract 2019;22:1241-51
|How to cite this URL:|
Oke O J, Oseni S B, Adejuyigbe E A, Mosaku S K. Pattern of attention deficit hyperactivity disorder among primary school children in Ile-Ife, South-West, Nigeria. Niger J Clin Pract [serial online] 2019 [cited 2020 Aug 9];22:1241-51. Available from: http://www.njcponline.com/text.asp?2019/22/9/1241/266172
| Introduction|| |
Attention deficit hyperactivity disorder (ADHD) is a developmental disorder that is characterized by hyperactivity, inattention, with or without impulsiveness-associated significant impairment in social, school, or work function not caused by any other mental disorder. These features must have been on for at least six months before age 12 years and occurring in at least two settings (school, home, etc.). The prevalent figures vary from 1% to 20%, with boys being more affected than girls.,, Studies on ADHD in Nigeria showed a prevalence of 8.7% in the South west, ranges from 7.6% to 23.15% in South East of Nigeria.,,
Children with ADHD lack concentration, do not complete assignment, forget things easily, and have poor writing and study skills. They lack attention to details, controlling impulses, and difficult in sitting down to focus on activity, social skills deficits, peer conflict, and behavioral/emotional problems., Children with ADHD experience problems with interpersonal relationships with family members and peers, and low self-esteem. They are also prone to injury and accidents, substance abuse, deficits in skill attainment, and subsequent low productivity.
Researches in different parts of the world done have used either teachers' or parents' disruptive behavioral disorder rating scale (DBDRS) to arrive at ADHD prevalence, but none used both parents' and teachers' DBDRS simultaneously to diagnose ADHD. In this study, pupils who were agreed by both parents and teachers DBDRS were considered to truly have ADHD. This study aimed at accurately determining the prevalence of ADHD among primary schools children in Ile-Ife using both parents and teachers DBDRS. Early recognition and intervention are also pertinent to good prognosis.,,
| Materials and Methods|| |
The survey was done among primary school children between the ages of 5–12 years in Ife Central Local Government Area, Ile-Ife. These pupils were selected using the multistage random sampling technique. The DBDRS was used in screening the pupils to identify children who had ADHD in accordance with DSM V. The sociodemographic characteristics of the pupils with ADHD and their peers without ADHD were determined. According to the 2006 National population census, there are 41,778 children aged 5–12 years in the local government area [21,907 (boys) and (19,871) girls] out of which 1,385 children were selected for the study. The study was done in second and third terms to ensure better behavioral assessment of the pupils by the teachers.
The procedures followed were in accordance with the ethical standards of Obafemi Awolowo University Teaching Hospital complex (OAUTHC) ethical committee and with the Helsinki Declaration of 1975, as revised in 2000. Approval for the study was obtained on December 12, 2013 to December 15, 2014 from the Research and Ethics Committee of OAUTHC, Ile- Ife, with protocol number ERC/2013/06/07. Permission was also taken from the Local Inspector of Education, head teachers, and class teachers from the selected schools. Written informed consent from the parents or guardian of the children that took part in the study was obtained while the pupils that participated gave assent.
Sample size determination
The sample size was determined using the Computer Programme for Epidemiological Analysis (CPEA) estimation of proportion  To guard against type I error (i.e. wrongly rejecting the null hypothesis when it is true) in the determination of the minimum sample size (N) for this study, the level of significance (α) which is the probability of making a type I error was set to a small value of 0.05 at a confidence level of 95%. By setting the beta level (β) which is the probability of making a type II error to 1.5%, power (1 − β) of 98.5% was used for the study. β is also the maximum acceptable difference from true proportion that can be tolerated or the level of type II error that can be tolerated. It was expected that with this very high study power, the calculated N will avoid the type II error (i.e. wrongly accepting the null hypothesis when it is false). Based on these statistical considerations, the sample size was determined using the formula for estimating proportions:
N = P (1 – P) Z2/β2
where P is the estimated prevalence of ADHD in primary school pupils. Based on the work of Ofovwe et al. in Benin, P was set at 8% (0.08). Z is the standard deviation from the true proportion of the disease and corresponds to 1.96 at 95% level of confidence. β was set at 1.5% (0.015) based on the calculated power for this study. N is the minimum sample size.
With the above formula, N was calculated to be 1257.
This sample size was increased by 10% to 1,385 so as to allow for possible missing and incomplete data.
All apparently healthy pupils between the ages of 5 and 12 years whose parents (guardians) gave consent.
Pupils outside the ages of 5 and 12 years and those whose ages could not be determined were excluded. Those pupils who declined to participate or whose parent (s)/guardian (s) did not give consent were not included. Pupils who are new in their present class as at the time of assessment and those on neuro stimulant or barbiturate were also exempted.
Multistage random sampling
Simple random sampling was used to select Ife Central local Government out of the two Local Governments in Ile-Ife. About 25% (18 schools) of the 72 primary schools in the area were selected by balloting. Pupils were selected from each school by sampling based on proportion to size of each selected school to the population of the 18 selected schools. Table of random number was used to select pupils from each class in each school.
DBDRS: The teachers' and parents' version of DBDRS  [Appendice I], [Appendice 2], [Appendice III] was used to screen pupils for ADHD as stated in DSM V [Appendix IV]. The DBDRS has nine-symptom criteria for hyperactivity, six-symptom criteria for inattention, three-symptom criteria for impulsiveness, and other symptoms' criteria for conduct disorder and oppositional defiant disorder. The parent version of DBDRS was translated to Yoruba using back translation method. The pupils that had ADHD symptoms' DSM V criteria for the diagnosis of ADHD from both parents' and teachers' DBDRS are considered to truly have ADHD. The parents and teachers of pupils who met the ADHD symptoms' criteria from the DBDRS screening were interviewed to obtain more information relating to the DSM V criteria using the teacher and parent interview questionnaire. The questionnaires were completed by the researcher and trained assistants. Information was obtained from the parents in English from the parents who understand English language and the Yoruba back translated questionnaire was used for the parents who only understand Yoruba language. The questionnaires were pretested before it was administered by the researchers. Parents' socioeconomic status was classified based on the method described by Oyedeji et al. The socioeconomic class was restratified into upper (I and II), middle (III), and lower (IV and V) social groups. A family that has more than four children is a large family and those with four children and below is small family.
Data handling and analysis
All the data from DBDRS and the sociodemographic characteristics data of the pupils were entered into SPSS version 15. Descriptive statistics was used to describe sociodemographic variables; mean scores were compared using Student's t-test and analysis of variance (ANOVA) as appropriate. Associations of proportions were tested using Chi-squared test, whereas other inferential statistics were used as appropriate. A P value of <0.05 was regarded as statistically significant. The internal consistencies of parents' and teachers' DBDRS were evaluated with Cronbach's alpha and was >0.7.
| Results|| |
Sociodemographic characteristics distribution of the pupils studied
In total, 1,385 pupils were recruited for the study. The age range of the subjects was 5–12 years with the mean ± SD of 8.3 (±2.1) years. About 53.1% pupils were aged 5–8 years and 46.9% were aged 9–12 years. In this study, 49.6% of the pupils were boys and 50.4% were girls giving a male-to-female ratio of 1:1.02. About 14.2% of the pupils were in the upper class, 56.5% were in middle, and 29.3% were in lower class. About 91.2% of the pupils came from large family and 8.8% from small family size.
Prevalence of ADHD among the pupils using teachers' DBDRS or parents' DBDRS and combined
ADHD was diagnosed in 140 (10.1%) pupils using the teachers' DBDRS, whereas 95 (6.9%) were diagnosed using the parents' DBDRS. Sixty-five (4.7%) of the 1,385 pupils were identified by both the teacher' and parent' DBDRS to have ADHD.
The age prevalence of ADHD and subtypes of ADHD in the study
The age prevalence of ADHD is shown in [Table 1]. The prevalence of ADHD among the different age cohorts ranged from 1.1% to 7.8%. It was highest in the 6-year age cohort and lowest among the 11-year age cohort.
|Table 1: Age prevalence of attention deficit hyperactivity disorder (ADHD) in 1,385 pupils studied|
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Prevalence of subtypes of ADHD is shown in [Figure 1]. Of the 65 pupils with ADHD, 28 (43%) had inattentive subtype, 25 (38.5%) had combined subtype, and 12 (18.5%) had hyperactive subtype.
|Figure 1: Prevalence of subtypes of attention deficit hyperactivity disorder (%)|
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Sociodemographic characteristics of the pupils with and without ADHD [Table 2]
|Table 2: Sociodemography of pupils with and without attention deficit hyperactivity disorder (ADHD)|
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About two-third of the pupils that had ADHD were aged 5–8 years, whereas one-third were aged 9–12 years. About 6.1% of the pupils aged 5–8 years had ADHD, whereas 3.1% of the pupils aged 9–12 years had ADHD. ADHD was more common in younger age (5–8 years) than the older age group (9–12 years). The difference in prevalence of ADHD among the age groups was statistically significant (χ2 = 7.153, P = 0.007). About 5.5% of the boys and 3.9% of the girls had ADHD with a male-to-girl ratio of 1.4:1. There was no statistically significant difference in gender, social class, family size, ethnicity, and ADHD prevalence.
Relationship between sociodemographic factors and prevalence of ADHD subtypes [Table 3]
|Table 3: Sociodemographic characteristics and prevalence of subtypes of attention deficit hyperactivity disorder (ADHD) in the 65 pupils with ADHD|
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All the subtypes of ADHD are more common in pupils aged 5–8 years compared with those aged 9-12 years. The combined subtype was the most prevalent in the younger age group, whereas the hyperactive subtype was the least common. For the higher age groups, the inattentive subtype was the most prevalent, whereas the hyperactive subtype was the least common. There was no statistically significant association between the age and ADHD subtypes (χ2 = 8.005, P = 0.237). All the subtypes of ADHD are more in boys than girls though the difference was not significant (χ2 = 0.592, P = 0.744). The most prevalent subtype of ADHD in boys is the combined subtype (ADHD - C), whereas the inattentive subtype (ADHD-I) was most prevalent among the girls. The combined subtype was the most common in upper and low social classes, whereas inattentive subtype was the most common in the middle social class (χ2 = 10.121, P = 0.115). Inattentive subtype was the most common subtype in all the religions (χ2 = 24.40, P = 0.803). Inattentive subtype was the most common subtype in both large and small families (χ2 = 2.609, P = 0.271). None of the above sociodemographic characteristics had significant association with prevalence of ADHD subtypes.
| Discussion|| |
The prevalence of 4.7% found in this study was <8.0% and 7.6% reported from Benin, in 2006 and 2007 by Ofovwe et al. and Ambuabunos et al., It was also <8.7% reported by Adewuya et al. from Ilesa, Osun State, in 2007. The difference could be as a result of the screening tool employed to arrive at diagnosis. The studies done in Benin made use of teachers DBDRS alone according to the DSM V criteria in arriving at the diagnosis of ADHD ,;however, a combination of teachers and parents DBDRS was used in this study. Some parents are biased in disclosing the hyperactive or inattentive behavior of their children while some teachers are impatient and nontolerance with their pupils thereby tagging them unduly to be hyperactive or inattentive. Hence, pupils that were agreed by both parents and teachers were considered to truly have ADHD to ensure absolute certainty of the diagnosis. Previous prevalence studies from other African countries did not use the full DSM V criteria except the study done in Congo and South Africa., The south African study by Mayer et al. found prevalence of 5.4% while Kashala et al. in Congo found 6.0%, which was similar to the prevalence of 4.7% from this study. The prevalence of 7.2% was reported from the meta-analysis studies done by Thomas et al. in USA. This is similar to that obtained in this study; hence, ADHD is as common in school age children in Nigeria, as in other parts of the world. The prevalence obtained in this study agreed with the world wide prevalence of 5.0% gotten by polanczyk et al. in worldwide meta-analysis study of ADHD.
There was no gender prevalence of ADHD in this study. The finding was similar to that of Kashala et al. in the study done in Congo and the study done by Cardo et al. in Spain in 2005. It was also said that girls are more often considered to be less overactive than boys, therefore more likely to be underestimated. Male preponderance was also found in some of the community-based studies done in Ilesha, Benin,, Puerto Rico, Australia, and South Africa ; hence, it is at variance with these studies.
In this study, inattentive ADHD subtype was the most common, followed by the combined subtypes and hyperactivity the least common. This finding is in agreement with what was found by Adewuya in Ilesha  and Ofovwe in Benin. The study done in South Africa by Mayer  also found the same trend. Some studies done outside Africa by other workers , also showed the inattentive type as the most prevalent subtype, followed by the combined subtype with hyperactivity the least common. It was only the study done by Kashala et al. in Kinshasa Congo that found combined subtype to be the most prevalent. The most prevalent subtype of ADHD in boys is the combined subtype (ADHD - C), whereas the inattentive subtype (ADHD-I) was most prevalent among the girls. This is also in agreement with the findings of Ambuabunos in Benin. The combined subtype was the most common in the upper and low socioeconomic classes, whereas inattentive subtype was the most common in the middle socioeconomic class. This was also in agreement with the findings of other workers., Inattentive subtype was the most common subtype in both large and small families. This was also in agreement with the findings of Abolfotouh.
ADHD was found to be more common in the younger age than the older age group in this study. The prevalence was higher among pupils aged 5–8 years than those aged 9–12 years. This finding is consistent with the study done in Puerto Rico in which a decline in the prevalence of ADHD with increasing age was found. Though the study done by Graetz et al. in Australia noted that within the age range of 6–12 years, no significant difference existed in the prevalence of ADHD.
This study is in keeping with those from Ethiopia where no sociodemographic correlates were found for ADHD among children. Prevalence of ADHD was also noticed to be low in pupils from large family size. This could be as a result of the protective effect of large family size on ADHD particularly in African setting where the practice of extended family is still in vogue. The result was contrary to the findings from the study on Manchester children attending ADHD clinics in which symptoms of ADHD were more common in large family size and ADHD.
In conclusion, the prevalence of ADHD from this study was 4.7%. Pupils needed to be screened with both parents' and teachers' DBDRS simultaneously to exclude misdiagnosis/over diagnosis of ADHD and its attendant social, medical, and financial costs. The inattentive subtype was the most prevalent, followed by the combined subtype and hyperactive subtype was the least prevalent from the study. Sociodemographic characteristics do not have significant association with ADHD prevalence.
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Conflicts of interest
There are no conflicts of interest.
Appendix IV: The criteria of symptoms for a diagnosis of ADHD DSM V:
In making the diagnosis, children still should have six or more symptoms of the disorder. In older teens and adults the DSM-5 states they should have at least five symptoms.
- Fails to give close attention to details or makes careless mistakes.
- Has difficulty sustaining attention.
- Does not appear to listen.
- Struggles to follow through on instructions.
- Has difficulty with organization.
- Avoids or dislikes tasks requiring a lot of thinking.
- Loses things.
- Is easily distracted.
- Is forgetful in daily activities.
- Fidgets with hands or feet or squirms in chair.
- Has difficulty remaining seated.
- Runs about or climbs excessively in children; extreme restlessness in adults.
- Difficulty engaging in activities quietly.
- Acts as if driven by a motor; adults will often feel inside like they were driven by a motor.
- Talks excessively.
- Blurts out answers before questions have been completed.
- Difficulty waiting or taking turns.
- Interrupts or intrudes upon others.
Combined inattentive and hyperactive-impulsive presentation:
- Has symptoms from both of the above presentations.
Reference: American Psychiatric Association (2013). Diagnostic and statistical manual of mental disorders (DSM-5), Washington, D.C.: American Psychiatric Association
Prepared by the National Resource Center on ADHD: A Program of CHADD (NRC). The NRC is supported through Cooperative Agreement Number CDC-RFA-DD13-1302 from the Centers for Disease Control and Prevention (CDC). The contents are solely the responsibility of the authors and do not necessarily represent the official views of CDC.
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[Table 1], [Table 2], [Table 3]