ADHD Among Rural Southeastern Nigerian Primary School Children: Prevalence and Psychosocial Factors

Abstract

Objective: To determine the prevalence of ADHD among primary school pupils in a rural community in Southeastern Nigeria and to determine the psychosocial factors associated with the condition. Method: One hundred eighty-one randomly selected participants had their teachers complete the school version of ADHD Rating Scale–IV. Their parents also completed a sociodemographic questionnaire, the clinical interview form for the child and adolescent ADHD patients, and home version of the ADHD Rating Scale–IV. Results: Twelve (6.6%) of the children met the criteria for diagnosis. A history of prolonged labor (odds ratio [OR] = 14.1; 95% confidence interval [CI] = [2.13, 93.1]), and parents’ negative assessment of their marriages (OR = 0.1; CI = [0.017, 0.567]) were the most predominant factors which independently associated with the ADHD in the children. Conclusion: There is, therefore, a need for the care of rural dwelling African children, who otherwise would have difficulties accessing health care that is concentrated in the cities.

Keywords

ADHD rural Nigerian school children prevalence psychosocial factors

Introduction

ADHD is one of the common behavioral disorders seen in child and adolescent psychiatric clinics (Homer et al., 2000). It affects children during the critical school age period. ADHD can interfere with the normal development of the school child, leading to school difficulties, academic under-achievement (Benjasuwantep, Ruangdaraganon, & Visudhiphan, 2002; Zentall, 1993), troublesome interpersonal relationship with family members and peers and low self-esteem (Schachar, Taylor, Wieselberg, Ghorley, & Rutter, 1987). Polanczyk, de Lima, Horta, Biederman, and Rhode (2007), in a systematic review, reported a world-wide prevalence of ADHD in about 5% of children. They opined that their findings should not be generalized to Africa and Middle East, as they contributed very few studies to their meta-analysis. Bakare (2012), in a review of African literature, found the prevalence of ADHD among African schoolchildren to range between 5.4% and 8.7%. Adewuya and Famuyiwa (2007) in the Southwestern and Ambuabunos, Ofovwe, and Ibadin (2011) in the south–south part of the country reported a prevalence of 8.7% and 7.6%, respectively, of schoolchildren having the disorder in an urban school setting. Egbochuku and Abikwi (2007) reported a prevalence of 23.15% in Benin City among schoolchildren, suggesting that there could be variations in the prevalence of ADHD among Nigerian children across the geopolitical zones. Like most other African studies (Adewuya & Famuyiwa 2007; Bakare, Ubochi, Ebigbo, & Orovwigho, 2010; Kashala, Lundervold, Sommerfelt, Tylleskar, & Elgen, 2006; Wait, Stanton, & Schoeman, 2002; Zeegers et al., 2010), these researchers explored the urban centers whereas available data revealed that the majority of children live in the rural areas (Ebiwolate, 2010). The prevalence of ADHD in most of the rural areas in Nigeria, therefore, is largely unknown.

A number of factors: Genetic and environmental have been reported as contributory to the etiology of ADHD (Biederman et al., 1995; Lou et al., 2004; Price & Raffelsbauer, 2012). It has been observed that among Nigerian children, psychosocial issues play a very important role in the etiology, course, and prognosis of several childhood psychiatric disorders (Gureje et al., 1994; Omigbodun, 2004). The factors associated with ADHD among children living in the rural areas are yet to be explored.

This study was designed to fill this gap in knowledge. It determined the prevalence of ADHD among pupils in primary school located in a rural area in the Southeast Nigeria and the psychosocial factors associated with the condition. We hope that this study would contribute to the extant corpus of knowledge in this area and thus guide formulation of policies aimed at improving mental health care delivery to the hard-to-reach rural dwellers.

Method

Design and Setting

This study was a cross-sectional descriptive epidemiological survey that was carried out in Ogberuru, a homogeneous Igbo speaking rural community in Orlu Local Government Area of Imo State in the Southeastern Nigeria.

Sample

A total of 200 schoolchildren, who picked “yes” in a balloting exercise and whose parents consented to participate in the study, were enrolled in the study. Nineteen of them, made up of 11 boys, and 8 girls with a mean age of 9.12 years were excluded from the analysis because their parents declined to complete the study; while the data from 181 of the participants, made up of 97 (53.6%) boys and 84 (46.4%) girls with a mean age of 9.39 years (SD = ±1.97), were subjected to analysis. The modal age group was 6 to 8 years and 42% of them fell within this age group. Most of them (65.2%) were living with both parents at the time of the study (see Table 1).

Table 1.

Sociodemographic Characteristics of Participants.

Variable	Frequency	%
Gender
Male	97	53.6
Female	84	46.4
Age (in years)
<6	1	0.6
6-8	76	42.0
9-11	73	40.3
12 and above	31	17.1
Type of family
Monogamous	157	86.7
Polygamous	20	11.0
Single parent	4	2.3
Family size
Small (<4 siblings)	26	14.4
Large (4 or more siblings)	155	85.6
Living condition
Lives with both parents	118	65.2
Lives with mother alone	21	11.6
Lives with father alone	—	—
Lives with grand parents	16	8.8
Other arrangements	26	14.4
Parent’s assessment of marriage
Very poor	7	3.9
Poor	28	15.5
Good	74	40.9
Very good	40	22.1
No comment	32	17.7
Fathers educational level
No formal/primary education	63	34.8
Secondary/tertiary education	118	65.2
Mothers educational level
No formal/primary education	80	44.2
Secondary/tertiary education	101	55.8

Instruments

The instruments used in the study included a sociodemographic questionnaire designed by the authors to collect information such as age, gender, religion, domicile, family size, birth order, and parental educational level; the clinical interview form for child and adolescent ADHD patients; and the school and home versions of the ADHD Rating Scale–IV.

The clinical interview form for child and adolescent patients was developed by Barkley (1991). The instrument obtains pregnancy-related information such as age, health of mother, and use of alcohol and other substances during pregnancy. There were also questions exploring early childhood factors such as the developmental milestone and medical history.

The school and home versions of ADHD Rating Scale–IV were developed by DuPaul, Power, Ananstopoulos, and Reid (1998) and have been shown to have adequate psychometric properties for use as a screening, diagnostic, and treatment outcome measures. It is an 18-item instrument in a 4-point Likert-type scale (not at all, just a little, pretty much and very much, with scores 0, 1, 2, and 3, respectively). The items of the questionnaire reflect the Diagnostic and Statistical Manual of Mental Disorders (4th ed.; DSM-IV; American Psychiatric Association, 1994) items for the diagnosis of the condition. The authors of the instrument have developed norms for the scores. This study, however, adopted the alternative method of interpretation in which a symptom endorsed to be “pretty much” or “very much” present is adjudged to be present. ADHD is adjudged to be present when at least six out of a possible nine symptoms in the inattentive domain or six out of a possible nine symptoms in the hyperactive–impulsive domains, or both must have been endorsed by both teacher and parent. Both versions of the instrument showed good internal consistency, with a Cronbach’s alpha of .89 for the school version and .88 for the home version. All the instruments were first, translated to Igbo language. Then, the Igbo versions were translated back to English language by another translator who is fluent in both English and Igbo languages. The original and the back-translated English versions were compared and were found to be very similar.

Procedure

Approval for the study was obtained from the ethical committee of the Jos University Teaching Hospital. The researchers also obtained the permission of the headmasters of the schools and held two meetings with the teachers. In the first meeting, the roles of the teachers in the study were explained and their consent to participate was obtained. The teachers also practiced how to fill the questionnaire with the right information about their pupils, and clarifications were given on areas that were not very clear to them. This exercise was done to ensure that they understood the items on the questionnaire very well to give the appropriate response to the questions. The schoolteachers well understood all the items of the instrument. In the second meeting, the children to be enrolled into the study were selected through balloting. In this process, “yes” or “no” were written on small pieces of papers that were folded and pooled into an open-ended sack for them to pick from it. Only those who picked the papers marked “yes” were enrolled. Their names were taken, and copies of the school version of the ADHD Rating Scale–IV were given to their teachers to complete. Letters requesting parents to come to the school with respect to the study were then distributed to the selected schoolchildren. The authors also took time to talk to the parents of the selected pupils who presented for the study about the illness and the relevance and nature of the study, following which they gave their consent to participate.

After obtaining the sociodemographic information from the parents, they were then interviewed with the sociodemographic questionnaire, the clinical interview form for child and adolescent patients, and the home version of the ADHD Rating Scale–IV. The preferred version (Igbo or English) of the questionnaires were administered by one of the authors, ACN, who is fluent in both Igbo and English languages. Home visits were scheduled to reach those parents who did not turn up for the school visits. The parent information was adjudged to be unavailable when the parents were not reached after three visits.

Data Analysis

The data so collected, which were double-checked for accuracy, were analyzed using the Statistical Package for the Social Sciences (SPSS) version 16 (SPSS Inc., 2008).

The frequency tables were run for relevant variables. Chi-square tests were used to test the differences between categorical variable and their associations in a cross tabulation. However, in instances where a cell has an expected frequency of less than 5, the Fisher’s exact test was computed. The factors that showed a significant association with ADHD diagnosis were entered into a logistic regression analysis.

Result

Prevalence of ADHD

Twelve (6.6%) of the children met the criteria for diagnosis of ADHD in both home and school settings. As shown in Table 2, the inattentive and the combined subtypes of ADHD accounted for 41.7% of the cases, respectively, with the hyperactive–impulsive subtype accounting for 16.6% of them. There was no significant difference in the gender of the children with ADHD. Eight (66.6%) of the children with ADHD were males compared with 4 (33.3%) who were females (χ² = 1.377, p = .241).

Table 2.

The Distribution of the ADHD Subtypes.

Subtype	Frequency	%
Hyperactive–impulsive	2	16.6
Inattentive	5	41.7
Combined	5	41.7

Association of Family Characteristics With Diagnosis of ADHD

Table 3 shows the association of several family characteristics with diagnosis of ADHD. Eleven (9.5%) of the children from large-sized families had ADHD compared with about 2% of children from small-sized families, and this tended toward statistical significance (p = .058). Family type (p = .140), birth order (p = 1.00), current marital status of parents (p = .323) and children’s living arrangement (p = .384) did not show a significant association with diagnosis of ADHD among the children. However, the parents’ assessment of their marriage shows significant association with their children being identified as having ADHD with 14.3% of children whose parents assessed their marriage as being poor/very poor having ADHD compared with 2.8% of those who reported their marriage as being good/very good (p = .018).

Table 3.

Association of Family Characteristics With ADHD.

Variable	ADHD, n (%)	No ADHD, n (%)	p value
Family size
Small (<4 siblings), n = 66	1 (1.5)	65 (98.5)	.058^a
Large (>4 siblings), n = 115	11 (9.5)	104 (90.5)
Family type
Monogamous, n = 157	9 (5.7)	148 (94.3)	.140^a
Polygamous, n = 20	3 (15.0)	17 (85.0)
Birth order
High (first to third), n = 122	8 (6.6)	114 (93.4)	1.000^a
Low (fourth and above), n = 59	4 (6.8)	55 (93.2)
Current marital status of parents
Currently married, n = 130	7 (5.4)	123 (94.6)	.323^a
Currently not married, n = 51	5 (9.8)	46 (90.2)
Parent’s assessment of marriage
Poor/very poor, n = 35	5 (14.3)	30 (85.7)	.018^a
Good/very good, n = 114	3 (2.8)	111 (97.4)
Living arrangement
Lives with parents, n = 155	9 (5.8)	146 (94.2)	.384^a
Other arrangements, n = 26	3 (11.5)	23 (88.5)

Fisher’s exact test.

Association of Pregnancy, Delivery, and Early Childhood History With Diagnosis of ADHD

As shown in Table 4, the health of mothers during pregnancy (p = .824), complication following delivery (p = .183), and method of delivery (p = .624) did not show a significant association with the diagnosis of ADHD. However, prolonged duration of labor was significantly associated with the diagnosis of ADHD, with 14.8% of children of mothers who recalled having prolonged labor being identified as having ADHD compared with 4.5% of children whose mothers recalled the duration of their labor as normal (p = .012). Developmental milestones (p = .540), sleep difficulties in childhood (p = .602), and history of childhood illness (p = .280) did not show a significant association with ADHD. The activity level in childhood was significantly associated with ADHD, with 19% of children seen as not active diagnosed with ADHD compared with 5% of those seen as active (p = .036).

Table 4.

Association of Pregnancy, Delivery, and Early Childhood History With Diagnosis of ADHD.

Variable	Has ADHD	No ADHD	p value
Health of mother during pregnancy
Good, n = 100	7 (7.0)	93 (93.0)	.824
Not good, n = 81	5 (6.2)	76 (93.8)
Duration of labor
Normal (<24 hr), n = 154	7 (4.5)	147 (95.5)	.012^a
Prolonged (>24 hr), n = 27	4 (14.8)	23 (85.2)
Complication following delivery
No complication, n = 158	9 (5.7)	149 (94.3)
Has complication, n = 23	3 (13.0)	20 (87.0)	.183^a
Method of delivery
Normal delivery, n = 149	10 (6.7)	139 (93.3)	.642^a
Assisted delivery, n = 32	2 (6.3)	30 (93.7)
Milestone achievement
Normal milestones, n = 170	11 (6.5)	159 (93.5)	.540^a
Delayed milestone, n = 11	1 (9.1)	10 (90.9)
Infancy feeding problem
Did not have feeding problem, n = 157	8 (5.1)	149 (94.9)	.057^a
Had feeding problem, n = 24	4 (16.7)	20 (83.3)
Sleep difficulties
No sleep difficulties, n = 133	9 (6.8)	124 (93.2)	.602^a
Had sleep difficulties, n = 48	3 (6.3)	45 (93.7)
Activity level in childhood
Active, n = 160	8 (5.0)	152 (95.0)	.036^a
Not active, n = 21	4 (19.0)	17 (81.0)
Past history of childhood illness
Not present, n = 112	6 (5.4)	106 (94.6)	.280^a
Present, n = 69	6 (8.7)	63 (91.3)

Fisher’s exact test.

A history of prolonged labor (odds ratio [OR] = 14.1; 95% confidence interval [CI] = [2.13, 93.1]) and parents’ negative assessment of their marriages (OR = 0.1; CI = [0.017, 0.567]) were the factors that were most strongly and independently associated with having ADHD in the children.

Discussion

This study adds to the literature on ADHD by focusing on the rural population in one of the three major ethnic groups in Nigeria. The prevalence rate for ADHD as found in this study is comparable with what have been reported in other parts of the world (Pineda, Lopera, Palacio, Ramirez, & Henao, 2003; Vasconcellos et al., 2003). Studies in different parts of Nigeria (Adewuya & Famuyiwa, 2007; Ambuabunos et al., 2011), despite the differences in the setting, reported similar findings. The prevalence rate reported in this study, however, was markedly lower than what was reported by Egbochuku and Abikwi (2007) who found a prevalence of 23.15% in Benin city, Edo State, south–south Nigeria among primary school children. Lahey et al. (1994) have opined that various factors could influence the prevalence of ADHD reported in several studies. Apart from the differences in the study settings, as in this study that was done among rural schoolchildren, other studies that had based their assessment on only one informant have been found to report higher prevalence rates of ADHD.

The hyperactive–impulsive subtype accounting for the least (16%) of the cases as found in this study is at variance with that reported in other studies where the hyperactive–impulsive subtype is reported to be the most prevalent (Montiel-Nava, Pena, & Montiel-Barbero, 2003; Rowland et al., 2001). Some of these studies that reported the preponderance of the hyperactive–impulsive subtype has been criticized for being clinic-based studies thus likely to have referral bias. This study, however, tends to agree with the findings of some other Nigerian school-based studies (Ambuabunos et al., 2011; Egbochuku & Abikwi, 2007) that reported preponderance of the inattentive subtypes of the disorder. The similarity of the settings for these studies could have accounted for this.

None of the children identified in this study has assessed care for the problem; this may be a reflection of the scarcity of health care resources among other factors that limit access to mental health care in the rural areas. According to the World Health Organization Assessment Instrument for Mental Health Systems (WHO-AIMS) report, there are no beds in community-based inpatient units, reserved for children and adolescents (WHO and Ministry of Health, 2006). The results of this study, therefore, suggest that even though children in rural areas are having this condition at a rate comparable with that found in the cities, yet they are less likely to be detected or treated. There is, therefore, need to plan for programs that would take mental health services to our rural communities to address the mental health challenges of rural dwellers.

Most of the family-related factors such as the size and family type which have been shown to be significantly associated with the diagnosis of ADHD in other studies (Biederman, Faraone, & Monuteaux, 2002), failed to be replicated in this study except for the parents’ negative assessment of their marriages. The finding that parent’s negative assessment of their marriages being significantly associated with a diagnosis of ADHD reflects the stress associated with a dysfunctional family even in a thriving extended family setting. Although dysfunctional family setting has been associated with a number of childhood mental health problems including ADHD, it is not clear that the nature of this relationship since having a child with ADHD could be stressful (Kaplan, Crawford, Fisher, & Dewey, 1998).

It is worrisome that prolonged labor associated with ADHD in this study. This worry is because many women still do not have access to adequate maternal care during pregnancy and delivery, and as reported by Mutihir and Utoo (2011), perinatal morbidity is still high in Nigeria. Gerring et al. (1998) has observed that in children with mild and moderate head injury, psychosocial adversity increased the chances that ADHD will develop. Prolonged labor increases the likelihood of a child sustaining perinatal injuries and maternal mortality and morbidity with the attendant negative consequences on the health of children have continued to be topical issues in the developing countries. It is, therefore, very crucial and of public health importance that perinatal injuries be minimized to improve the health of children. There is a need for more comprehensive, community-based maternal and child health programs in the country, especially in the rural areas. This health programs would require health policies that would address the health needs of the rural dwellers. The findings of this study would contribute in informing such policy formulations.

Limitations

The results of this study cannot be generalized to the entire country or people of Southeastern Nigeria. The number of children with ADHD is relatively small. The use of only one instrument for the assessment of ADHD in the children is also a limitation in this study. However, assessing both parents and teachers is strength of the study. The parent report relies heavily on recall of events in the past and, therefore, is subject to recall bias. The Igbo versions of the instruments that were used were not standardized and this could affect the result of the study.

Recommendations

A large community-based study group would be needed to validate the findings of this study, as well as the use of observation and other methods of assessments to improve the quality of the study.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Author Biographies

A. C. Ndukuba is a lecturer/consultant psychiatrist at University of Nigeria Enugu Campus with major interest in child psychiatry.

P. C. Odinka is a lecturer/consultant psychiatrist at University of Nigeria Enugu Campus with interest in social psychiatry.

R. C. Muomah is a clinical psychologist and has a PhD in clinical psychology.

J. T. Obindo is a lecturer/consultant psychiatrist with the University of Jos.

O. O. Omigbodun is a professor of child psychiatry with University of Ibadan.

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