A STUDY OF ASPECTS OF ACADEMIC PERFORMANCE AND
ITS DETERMINANTS AMONG PRIMARY SCHOOL CHILDREN
WITH ASTHMA ATTENDING THE UNIVERSITY OF NIGERIA
TEACHING HOSPITAL, ENUGU, NIGERIA
A DISSERTATION SUBMITTED TO THE NATIONAL POSTGRADUATE
MEDICAL COLLEGE OF NIGERIA IN PARTIAL FULFILMENT OF THE
REQUIREMENTS FOR THE AWARD OF FELLOWSHIP IN THE
FACULTY OF PAEDIATRICS
BY
NDUAGUBAM OBINNA CHUKWUEBUKA MBBS 2004
May 2015
0
DECLARATION
I hereby declare that this work is original unless otherwise acknowledged. The work has neither been presented to any other College for Fellowship nor has it been submitted anywhere for publication.
…………………...... DR. NDUAGUBAM, OBINNA CHUKWUEBUKA
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ATTESTATION
We hereby certify that this work was carried out by Dr. Nduagubam O. C. under our supervision.
We have also supervised the writing of the dissertation.
……………………………………….. DR. T. OGUONU, FMCPaed Senior Lecturer / Consultant Pediatrician Department of Pediatrics, University of Nigeria Teaching Hospital, Ituku/Ozalla, Enugu State.
……………………………………….. DR. N. OJINNAKA, FWACP Professor / Consultant Pediatrician Department of Pediatrics, University of Nigeria Teaching Hospital, Ituku/Ozalla, Enugu State.
……………………………………….. DR. R. IBEKWE, FMCPaed Senior Lecturer / Consultant Pediatrician Department of Pediatrics, University of Nigeria Teaching Hospital, Ituku/Ozalla, Enugu State.
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DEDICATION
This work is dedicated to children with asthma all over the world, to my wife, Tersy and our children, Ikenna, Chioma and Inya-Ishor.
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ACKNOWLEDGEMENT
I owe a special gratitude to my supervisors, Dr T. Oguonu, Prof N. Ojinnaka and Dr R. Ibekwe for their approachability and guidance towards the successful completion of this work and for their inspiration which was a source of strength to me throughout this study.
My acknowledgement also goes to Prof B. Ibe, Prof G. Adimora, Prof I Emodi, Dr. N Ikefuna,
Dr. A. Ubesie, Dr. E. Aronu, Dr. H. Obu, Dr. B. Tagbo, Dr. A. Ayuk, Dr. O. Ezenwosu, Dr. J.
Eze, Dr B. Edelu, Dr. C. Eke and Dr J Chinawa, all Consultant Pediatricians in the Department of Paediatrics UNTH, for their concern and suggestions during the study.
This study would not have been possible without the co-operation of the head teachers and teachers of the various schools visited during data collection as well the tireless efforts of my statistician, Mr. Ikenna Uche. I am truly indebted to them.
I am grateful to my parents, Aji Nv’ Owa, Igwe and Nono Nduagubam, who gave my effort the needed blessing. I wish to acknowledge my wife, Theresa Agbo Nduagubam, for her understanding and sacrifice throughout this work.
Finally, I thank God Almighty for His constant love, preservation and strength.
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TABLE OF CONTENTS Pages
DECLARATION ...……………………..……………… i
ATTESTATION ………………………..……………… ii
DEDICATION …………………………..…………… iii
ACKNOWLEDGEMENT ……………………………………….. iv
TABLE OF CONTENTS ……………………………………….. v
LIST OF TABLES ……………………………………….. vi
LIST OF FIGURES ……………………………………….. viii
LIST OF ABBREVIATIONS ……………………………………….. ix
SUMMARY ………………………………………... x
INTRODUCTION ...……………………………………… 1
LITERATURE REVIEW ………………………………………… 3
AIM AND OBJECTIVES .………………………………………... 20
METHODOLOGY .………………………………………... 21
RESULTS .………………………………………... 31
DISCUSSION .………………………………………... 61
CONCLUSION .………………………………………... 71
LIMITATIONS OF THE STUDY .……………………………….……….. 72
FUTURE RESEARCH NEED ……………………………………..….. 73
REFERENCES ...………………………..……………... 74
APPENDICES ..……………………………………….. 83
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LIST OF TABLES Pages
Table I: Age and sex distribution of the subjects and control 33
Table II: Comparison of median overall and specific subjects scores of subjects and controls 36
Table III: Comparison of median overall and specific subjects scores of male subjects and controls 37
Table IV: Comparison of median overall and specific subjects scores of female subjects and controls 38
Table Va: Comparison of academic performance of male and female subjects 39
Table Vb: Comparison of median overall and specific subject scores of male and female subjects. 39 Table VIa: Comparison of academic performance of male and female controls 40
Table VIb: Comparison of median overall and specific subject scores of male and female controls 40 Table VII: Age specific comparison of median overall scores between subjects and controls 41
Table VIII: Comparison of academic performance and asthma control of subjects 43
Table IX: Age specific comparison of academic performance and asthma control of subjects 44
Table X: Comparison of asthma control and school absence among subjects 48
Table XI: Association between academic performance and number of days of absence of subjects and controls 49
Table XII: Age specific comparison of school absence between subjects and controls 50
Table XIII: Mean ± SD overall and gender-related DAPQ scores of subjects and control 52
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Table XIV: Age specific comparison of mean DAPQ scores of subjects and controls 53
Table XV: Relationship between academic performance and socio-economic class in subjects and controls 56
Table XVI: Multiple linear regression result of predictors of academic performance in subjects 58
Table XVII: Multiple linear regression result of predictors of academic performance in controls 59
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LIST OF FIGURES Pages
Figure 1a: A scatter diagram showing the relationship between IQ and academic performance among subjects 54
Figure 1b: A scatter diagram showing the relationship between IQ and academic performance among controls 54
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LIST OF ABBREVIATIONS ACT – Asthma Control Test ACSS – Asthma Control Scoring System ACQ – Asthma Control Questionnaire ANOVA – Analysis of Variance ATAQ – Asthma Therapy Assessment Questionnaire ATS – American Thoracic Society C-ACT – Childhood Asthma Control Test DAPA – Draw-A-Person Age DAPP – Draw-A-Person Point DAPQ – Draw-A-Person Quotient DAPT – Draw-A-Person Test ERS – European Respiratory Society GINA – Global Initiative on Asthma IQ – Intelligence Quotient LASS – Lara Asthma Symptom Scale MAP – Missouri Assessment Program PIAT – Peabody Individual Achievement Test PACT – Palmetto Achievement Challenge Test SB – Stanford- Binet SPM – Standard Progressive Matrices SPSS – Statistical Package for Social Sciences UNTH – University of Nigeria Teaching Hospital WHO – World Health Organization WISC – Wechsler’s Intelligence Scale for Children WJ – Woodcock–Johnson WRAT – Wide Range Achievement Test ix
SUMMARY
There is a paucity of data on the academic performance of Nigerian children with asthma. In order to address this gap in knowledge, this study examined aspects of the academic performance of children with asthma in Enugu, Nigeria with the aim of determining the influence of asthma on school absence rate, intelligence quotient (IQ) and socio-economic status.
The academic performance, intelligence quotient and school absence rates of 120 children with asthma (subjects) and that of age-, sex- and socio-economic class- matched children without asthma (controls) attending primary schools in Enugu metropolis were studied. The overall academic performance as well as performance in selected key subjects was assessed using scores achieved in examinations in the 2012/2013 academic year. Intelligence quotient was assessed using the Draw-A-Person Test (DAPT) while school absence rate was extracted from the class attendance register. Socio-economic class was ascertained using the classification by Oyedeji while the level of asthma control in the subjects was assessed using the Childhood Asthma
Control Test (C-ACT).
Statistical Package for Social Sciences (SPSS) software for Windows® version 19.0 (IBM Inc
Chicago Illinois USA, 2011) was used for analysis. Descriptive statistics such as mean and median were obtained for continuous variables while categorical variables were summarized using frequencies and percentages. The comparison of means of IQ that was normally distributed was done using Student’s t-test and Analysis of Variance (ANOVA) while other variables that were not normally distributed such as Academic performance and school absence were compared using the Mann-Whitney U test. Association between categorical variables was determined using chi-square. Level of significance was set at p < 0.05.
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The median (range) overall academic scores for the subjects and controls were 79.04% (36.08% -
99.57%) and 80.01% (50.65% - 97.47%), respectively. The difference was not statistically significant (U = 6804, p = 0.461). There was also no significant difference in the academic performance of subjects and controls in selected subjects: - English Language (U = 6408, p =
0.141), mathematics (U = 6633, p = 0.292), science (U = 7074, p = 0.815) and social studies (U
= 6151, p = 0.051). The overall academic performance of subjects with poor asthma control was not significantly different from that of those with good control (U= 1235, p = 0.486).The subjects had more days of absence from school (U = 5103, p = < 0.001) compared to controls.
School absence had no significant relationship with academic performance among subjects (x2 =
3.915, d.f = 2, p = 0.141) and controls (x2 = 0.586, d.f = 1, p = 0.444).
The IQ of the subjects (123-28 ± 21.45) did not differ significantly from those of controls
(118.41 ± 19.87; t = 1.826, p = 0.069). There was a significant positive correlation between IQ and academic performance among both subjects (r = 0.218, p = 0.017) and controls (r = 0.308, p
= 0.001). There was also a significant positive correlation between socio-economic class and academic performance among the subjects (r = 0.194, p = 0.034) but not for controls (r = -0.122, p = 0.185). However, multiple regression analysis showed that asthma control had a significant positive effect on academic performance of the subjects (B = 1.080, p =0.003) while age had a significant negative effect on academic performance (B = -3.776, p < 0.001). IQ, socio-economic class and school absence rates had no significant effect on the academic performance of the subjects
In conclusion, the academic performance of the subjects compares favorably with that of children without asthma. Asthma control has a significant effect on academic performance of the subjects but not IQ, socio-economic class or school absence rates. xi
INTRODUCTION
Asthma is one of the most common chronic illnesses among children, affecting over six million children globally.1 Children with asthma, similar to children with other chronic illnesses, are at the intersect of the health and education systems and are expected to compete with non-asthmatic counterparts in the same classroom under the same learning conditions.2 At school, their health needs may be attended to by a school nurse, while their educational needs may be overlooked or under-estimated.3
The restriction from normal activities due to recurring, episodic attacks in children with asthma can impact significantly on the quality of life and increase the burden due to asthma.4 Frequent attacks in children with poor asthma control also leads to a significant number of days of absence from school and this can affect their academic performance.5, 11
Although frequent school absences may mean that children with asthma could perform poorer academically than those who do not have the condition, 5, 9 the impact of asthma on academic performance is relatively unexplored. In addition, the results of the studies that have been conducted vary even within the same country.5, 6, 12, 13 Thus while some studies6, 13, 14 found that the disease process has no negative effect on academic performance, others 12, 15 reported significant negative effect of asthma on academic performance. Associations have also been suggested between asthma and learning disabilities, 15 reading problems, 16 grade repetition, 17 and behavioral problems.18-20
Most of the studies 6, 12, 14 on asthma and academic performance in children with asthma have been in developed countries and despite the high prevalence of asthma among Nigerian school children, 21, 22 there has been no study to my knowledge to determine the impact of asthma on
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academic performance in our environment. However, considering the socioeconomic and educational situation in Nigeria, the academic performance of children with asthma could be different from that of those in developed countries as academic performance of children with other chronic disease conditions such as epilepsy, 23 sickle cell disease24, 25, 26 and behavioral disorders27 in Nigeria have shown.
This study was therefore done to determine the impact of asthma on the academic performance of school children and the associated factors. The results are expected to contribute to the development of school health programs for children with asthma in Nigeria.
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LITERATURE REVIEW
Historical Background
The Corpus Hippocraticum, written by Hippocrates in 450BC is regarded as the earliest text where the word asthma is used as a medical term.28 In the text, he stated that spasm linked to asthma was more likely to occur among anglers, tailors and metalworkers.28 Galen (130-200
AD), an ancient Greek physician, described asthma as bronchial obstruction and treated it with owl's blood in wine.28 Jean Baptiste Van Helmont (1579-1644 AD) said that asthma originates in the pipes of the lungs while Bernardino Ramazzini (1633-1714 AD) detected a link between asthma and organic dust and also recognized exercise-induced asthma.28 In 1873, Thorowgood29 published a paper which tried to explain the pathophysiology of the disease. During the third to fifth decades of the 20th century, asthma was seen as one of the “holy seven” psychomatic illnesses because its etiology was considered to be psychological and psychoanalysts interpreted the asthmatic wheeze as the suppressed cry of the child for its mother.28
In the latter parts of the 19th century and up to the middle of the 20th century, various types of treatment were recommended for asthma28, 30-33 based on the prevailing understanding of the disease and its pathogenesis. These treatment modalities were aimed at cure and reduction of the burden of the disease. During these times, the effect of asthma on everyday life was not given much attention due probably to the prevailing lifestyles. As development progressed, the impact of morbidity on life style was increasingly recognized and related to life disability indices. In consequence, further understanding and measures to ameliorate the effect of the disease was sought both for the adult and paediatric populations. Among children, efforts to understand the
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impact of the disease was directed towards understanding the disease impact on the quality of life such as school absences and academic performance.13-20
Epidemiology
Asthma affects all age groups, race and sex34, 35and an estimated 300 million people have asthma worldwide.36 It is one of the most common chronic diseases of childhood affecting more than 6 million children globally.36 Previous studies1, 37 have noted an increase in the prevalence of childhood asthma worldwide associated with a rise in the global burden of asthma. However, recent epidemiological studies suggest that the prevalence of asthma may now be declining in some parts of the world.4, 38 This decrease in the prevalence of childhood asthma is attributed to ever- improving medications which has brought about progress in its clinical management and control.36 Also asthma awareness / education work provides information and support which has improved the understanding and management of this condition for thousands of people.4,36
Schayck and Smit38 using epidemiological data in Netherlands noted a downward trend in the prevalence of asthma. They postulated that a more likely reason for decline in the prevalence of asthma was improved diagnostics followed by correct treatment.38
Globally, the prevalence varies widely from one area to another, ranging from as low as 1.6% in
Ethiopia to as high as 36.5% in the United Kingdom.4 Prevalence data however, are lacking for many countries in Africa although nearly 50 million Africans are currently estimated to have asthma.1
Childhood asthma seems to be more common in modern metropolitan areas compared to rural areas of developing countries.4, 35 In Algeria for example, more than five times as many people in the urban areas have asthma compared to the rural areas.1 In Nigeria, reports 21, 22, 39, 40 are limited
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to urban areas and no study has found any difference in prevalence between children from the urban areas in different regions of the country. Thus while Falade et al 21 reported a prevalence of 7.2% from Ibadan, Okoroma 22 reported a prevalence of 7.1% from Enugu among school children. Both studies by Falade 21 and Okoroma 22 were hospital-based and were done in similar urban settings in Nigeria. Boys are more affected than girls before puberty, but by the third decade, the prevalence becomes equal and subsequently, more women than men are affected.41,
42The smaller lung volume in males at birth, which becomes larger in adulthood, may be a factor.21
Asthma imposes a major functional disability on its sufferers.4, 43 It is one of the most common causes of childhood emergency department visits, hospitalizations and missed school days.4
Asthma is also known to affect the psychological, physical and social well being of the patients.43,44
Pathogenesis
Airway inflammation occurs when genetically susceptible individuals are exposed to certain environmental factors such as cold, dust, smoke and pollen.45 The inflammation results from the release of inflammatory mediators and is associated with vasodilatation, edema, cellular infiltration with neutrophils, eosinophils, lymphocytes and mast cells, patchy desquamation and squamous metaplasia of the mucosa lining the lumen of the airway.41 Substance-P within the airway nerves is increased while vasoactive intestinal peptide is reduced.45 Airway narrowing occurs as a result of smooth muscle contraction, vasodilatation of bronchial vessels, edema of the sub-mucosal tissues and hyper-secretion of mucus into the lumen of the airway.4
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Clinical features
Children with asthma usually present with intermittent dry coughing and /or expiratory wheezing which can be worse at night.4 Other symptoms include shortness of breath and chest tightness or pain as well as other non-specific symptoms such as limitation of physical activity which makes it difficult for the child to keep up with the peers in physical activities.4 Signs that could be elicited include cough, noisy and or difficult breathing, chest in-drawing, rhonchi with or without crepitations, prolonged expiratory phase of respiration and decreased air entry or breath sounds on auscultation of the chest.4 In severe cases, a child with asthma may be restless, sweating and cyanosed and chest examination may reveal a silent chest.4 However, there may be no signs detectable between episodes of asthmatic attacks.40 Recurrent episodic attacks of asthma restricts the child from engaging in normal activities and can impact significantly on his quality of life, thus increasing the burden of asthma.4
Diagnosis
A correct diagnosis of asthma is essential if appropriate drug therapy is to be given while accurate assessment of asthma symptoms is critical in research and clinical practice.46, 47
According to the Global Initiative on Asthma (GINA), 46 the diagnosis of asthma is acceptable when made by a trained health care professional who notes symptoms consistent with asthma and objective evidence of variable airway obstruction, following the diagnostic criteria of GINA guidelines. Measurement of lung function (spirometry or peak expiratory flow) provides an assessment of the severity of airflow limitation, objective evidence of its reversibility and variability, as well as confirmation of the diagnosis of asthma.46
Treatment xvii
The major role of airway inflammation in childhood asthma has been recognized for decades and one of the goals of treatment is to reduce underlying inflammation, and decrease the daily symptom burden by preventing recurrent attacks thus achieving and maintaining clinical control.46 This requires proper diagnosis, adequate management of pro-inflammatory environmental exposures, use of appropriate anti-inflammatory medications and control of co- morbid conditions that can worsen asthma as well as regular follow up.46 Oviawe and
Osarogiagbon48 in their study on trend in asthma severity in steroid naive asthmatic children in
Benin city, Nigeria noted that those treated with steroid down –regulated and developed persistent asthma. This was a retrospective study in which case note of patients managed for asthma from 1985 to 1995 were reviewed. Due to poor use of steroid therapy they noted that
57.1% of children with asthma who initially had mild intermittent symptoms progressed to persistent asthma. Even though sample size was small (77 patients), this study was highly informative as regards treatment of asthma.
The aim of treatment should be to achieve and maintain control for prolonged periods.45, 49
However, management based on newer trends in childhood asthma is uncommon and adherence to management guidelines is still poor even amongst health care professionals.40, 50 Guideline- defined asthma control is achievable in most patients through proper assessment of the patient and the tailoring and adjustment of treatment in regular cycles based on asthma control status.46
When the condition is not controlled, asthma treatment is stepped up until control is achieved and maintained for at least three months, at which point a step down in treatment can be considered.46 However, studies 4, 47 have shown that despite the use of highly effective medications, exacerbations still occur with resultant effect on the individual and global disease burden.4
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Asthma status - severity and control
Asthma status involves both the severity of the disease and its responsiveness to treatment43 but there has been no widely accepted definition for asthma severity, control, or exacerbations.47 The
Joint Task Force of the American Thoracic Society (ATS) and the European Respiratory Society
(ERS) 47 however, recommend that asthma severity be defined as the difficulty in controlling asthma with treatment after exclusion of modifiable factors such as poor adherence, smoking, and co-morbidities. The Joint Task Force47 also defined asthma control to encompass not only the patient’s recent clinical state (symptoms, night waking, reliever use, and lung function), but also their “future risk”, that is, their potential for experiencing adverse outcomes, such as loss of control in the near or distant future, exacerbations, accelerated decline in lung function, or treatment-related side effects. Earlier GINA guidelines51 subdivided asthma by severity based on the severity of symptoms, airflow limitation, and lung function variability. Severity largely reflects the required level of treatment and the activity of the underlying disease state.47A major limitation of asthma classification using asthma severity is its poor value in predicting what treatment would be required and what the response to that treatment might be.6, 46
With growing recognition of the importance of the patient’s perspective and the limitations of the severity-based asthma classification, asthma guidelines have now identified asthma control as the focal concept.46 Control, in lay terms, may indicate disease prevention or even cure. However, in asthma where neither of these are realistic options at present, it refers to resolution of symptoms and elimination of disease variability.46 Classification based on control level is by far more practical, easier to follow, includes more clinically relevant issues and implies more appropriate decisions on the choice of treatment in a given patient with asthma.46 In addition, telling the
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patient that your asthma is controlled or not controlled is more informative than intermittent or persistent asthma, especially when such words are translated into the patient's own language.46
Both clinical practice and clinical trial have focused increasingly on assessing asthma control and several standardized measures for assessing clinical control of asthma have been developed.46, 52-56 These include the Asthma Control Questionnaire (ACQ), 52 Asthma Control
Scoring System (ACSS), 53 Asthma Control Test (ACT) and the Childhood Asthma Control
Test(C-ACT), 49 Asthma Therapy Assessment Questionnaire (ATAQ) 54 and the Lara Asthma
Symptom Scale (LASS).57 None of the instruments cover all relevant control characteristics, although most are aligned with guideline definitions of control.58 However, they demonstrate validity and responsiveness, with some measure of reliability.58 All are short and easily administered, easy to interpret, and have evidence to support their use in clinical decision making.58
ACT is one of the most widely used and is a short, simple, reliable, patient-based tool for identifying patients with poorly controlled asthma which is responsive to changes in asthma control over time. 49,58 In the clinical setting, the Childhood ACT (C-ACT) is a useful tool to help physicians identify children with uncontrolled asthma and facilitate their ability to follow the patient’s progress with treatment.58 A cut off score of 19 or less identifies patients with poorly controlled asthma. 58
Academic performance of children with chronic illnesses
Nettles24 reported that the academic performance of children with sickle cell disease is significantly lower than that of their age- and sex- matched comparison group. Similarly,
Ogunfowora et al 25 noted that Nigerian children with sickle cell anaemia were underachievers academically and that their underachievement was not due to school absence. In contrast, xx
however, Ezenwosu et al 26 reported that the academic performance of children with sickle cell anaemia was not significantly different from that of normal children. The difference in the findings between the study by Nettles and Ezenwosu could be due to differences in the study design and academic performance tool used, varying standards between institutions and teachers and differences in school systems in different environment. While Nettles24 studied a relatively smaller sample size (compared to Ogunfowora and Ezenwosu) of American children classified into two unequal parts based on forms of severity of sickle cell disease (SS and SC genotypes) and only looked at their performance in reading and mathematics; Ezenwosu et al 26 observed
Nigerian children with SS genotype and used performance in four key subjects (English language, Mathematics, Social studies and Sciences). Studies by Ogunfowora et al 25 and
Ezenwosu et al 26 were similar in sample size, both were hospital based, observed only children with SS genotype and used performance in four key subjects (English language, Mathematics,
Social studies and Sciences); however their findings were different. The difference in their findings 25, 26 could be attributed to the differences in the study design and environment where these studies were done. Ogunfowora et al 25 studied older children aged 6 to 17 years and had siblings within 3 year age difference as controls not matched for sex while Ezenwosu et al 26 studied younger children aged 5 to 11 years and used their school mates matched for age (within
6 months) and sex as controls. Although both studies were in Nigeria, that of Ogunfowora et al 25 was in the south-west part of Nigeria while Ezenwosu et al 26 did theirs in the south-eastern
Nigeria.
Ibekwe et al 23 also reported that the academic performance of children with epilepsy without other chronic disorders such as cerebral palsy, congenital heart disease and sickle cell disease was not significantly different from that of normal children in the same setting. Work by
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Ezenwosu et al was similar in design to that by Ibekwe et al was similar in design and finding but differed in the population of children studied. While Ezenwosu et al studied children with
SCA, Ibekwe et al worked on children with epilepsy. Also, Akpan and colleagues 27 in community- based study reported that children with behavioral disorders had worse academic achievement than controls although their school absence rate was not more than that of sex- and age-matched controls.
Academic performance of children with Asthma
Asthma in childhood has been shown to cause a significant loss of school days which is related to the frequency of episodes of exacerbation.5-10 Lenny 59 noted that one third of children with asthma have greater than 5 episodes of asthmatic attacks in a year. Frequent absence from school among children with asthma may mean that they do less well academically than those without asthma.5, 9 The impact of asthma on school performance/attainment is relatively unexplored and the findings in the studies that have been conducted differ.5, 6,12,13,15 While some studies12,15-17 documented lower academic performance in children with asthma, others 5,6,8,13,60 found no difference in the academic performance of children with asthma compared to those without.
In a cross sectional survey involving a population based sample of children from the United
States of America in grades 1 to 12, Fowler et al 15 noted a greater likelihood of grade failure among children with asthma compared with healthy children. Krenitsky-Korn12 reported that students with asthma scored lower in mathematics compared to their non-asthma colleagues. An association between asthma and learning disabilities, 15 reading problems 16 and grade repetitions, 17 has also been reported by other researchers.
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In contrast, Taras et al 5, in a review of published studies investigating childhood asthma and student performance at school, reported that there was either only a weak or non-existent association between asthma and school achievement. Silverstein et al 8 also reported that there is no difference in academic performance between asthmatics and non-asthmatics. In fact, Gutstadt and his colleagues13 in a study of children chronic asthma, found that overall, the academic capabilities of children with asthma were average to above average. In addition, Le louarn and coworker 60 reported that asthmatics were not at higher risks of school problems and that development of preventive programs that focus on school problems of asthmatic children was not needed. Furthermore, Moonie et al 6 in a population-based study noted that generally children with asthma perform the same academically as their non-asthmatic peers although those with persistent asthma show a trend of performing poorer on the Missouri Assessment Program
(MAP).
The inconsistency in the results of these studies on the relationship between asthma and academic performance could be attributed to differences in the diagnosis of asthma and definition of school performance. In addition, whether the analysis accounted for asthma severity, the inclusion of a control group, and the use of standardized versus caregiver-reported measures of school performance may also account for these differences. Studies by Fowler et al
15 and Krenitsky-Korn12 though well controlled and population-based, did not put in to perspective asthma severity of their study population when compared to other studies. 6, 13, 60
Also study by Taras et al 5 was a review of a number of published works on academic performance of children with asthma with differences in diagnosis of asthma, definition of asthma status and the academic performance tools used. Silverstein et al 8 in his cohort study of children with asthma had age- and sex- matched controls but did not match for socio-economic
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class and did not consider asthma severity or control. Most of these studies6, 12, 13, 60 also recommend further research on the relationship between asthma and academic performance.
Factors that May Influence the Academic Performance of Children with asthma
School absence
Increased absenteeism by school children with asthma has been well documented.5, 12, 13, 61, 62
Asthma has been reported to be the most common cause of school absenteeism among chronic health conditions in childhood. 5,12,13,61-65 Absenteeism has been related to lower grades at school and academic achievement and to psychological, social and educational maladjustments.66
School absence is a good predictor of academic attainment.5, 66 Multiple, brief and prolonged absences can interfere with a child’s ability to effectively follow the processes of knowledge acquisition.67 Weitzman and colleagues68 stated that children who are frequently or persistently absent from school tend to perform poorly and were likely to drop out before graduation from high school. For effective school performance, especially in academics, a child should attend regularly in order to follow effectively the processes of knowledge acquisition as well as other activities.68 Weitzman68 recommended that greater than 12 school days’ absence from school in a year should be regarded as high school absence and 1-12 school days’ absence as low school absence.
Although school absence in children with asthma has been studied, the relationship between school absence and academic performance in children with asthma is still unclear.5,6,8,12,13
Children with persistent asthma experience recurring episodes of absenteeism, which may contribute to decreased school performance.8 Being away from school was linearly associated with low scores on standardized mathematics tests among children with asthma.69 This finding xxiv
was collaborated by Baxter et al 66 and Moonie et al 6 who observed an inverse relationship between absenteeism and academic attainment among children with asthma. However, Gutstadt and colleagues13 reported that among children with asthma, school absenteeism was not associated with academic performance. The difference between the reports may be due to differences in the academic attainment tools used and the age groups studied. Thus while Baxter et al 66 used Palmetto Achievement Challenge Test (PACT) scores, Moonie et al 6 used Missouri
Achievement Program (MAP) scores and Gutstadt et al 13 a standardized achievement test in reading and Mathematics and whereas Baxter et al 66 and Gutstadt et al 13 studied younger children in elementary school, Moonie et al 6 worked on older children aged 8-17years. Also, although the three studies were from the USA, they were done in different parts of the country.
Severity/control of asthma
Studies on the effect of asthma status on academic performance are few and the independent contribution of asthma status, if any, to academic performance of children with asthma has been poorly explored.10 While Gonzales-Macias70 reported a weak association between well- controlled asthma and good classroom performance, Moonie et al 6 noted that persistent asthma negatively affects academic performance. Although Gonzales-Macias70 used asthma control and
Moonie et al 6 assessed asthma severity, their findings were similar. These studies6, 70 also suggested that poor asthma status caused poor academic performance through increase in school absence. However, Daphne71 in a more recent study has identified poor sleep quality in these children due to poorly controlled asthma as the cause of this observed negative effect of poor asthma status on their academic performance. No studies to the best of my knowledge have been
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done on the relationship between asthma status and academic performance among children with asthma in our environment.
Socio-economic status
Asthma is one of the few diseases reported to be commoner in the higher social classes 4, 72 but atopic asthma and severe asthma are commoner in the lower socio-economic classes.72 Severe asthma with increased hospitalization and death has been linked to poverty, ethnic minorities, and urban living.4 Children with asthma from deprived areas are reported to be more likely to miss school than their more affluent peers, and minority ethnic children are also more likely to have poor school attendance.73
The relationship between socioeconomic status and academic performance amongst children with asthma however has been poorly studied and reports from available research vary. Karadel and colleague74 reported that poor school performance is higher among children from poor socio- economic background and attributed it to poor motivation; unsatisfactory home environment and neglect; poor housing and nutrition.74 Similar findings to that of Karadel and colleague were reported by Ong et al 75 from Malaysia and by Ozmert and Colleagues76 from Turkey. However the finding was not in support of an earlier report by Guststadt and colleagues13 who reported that socioeconomic status was not associated with low academic performance amongst children with asthma. While Gutstadt et al 13 study was on children with asthma, the studies by Karadel and his colleague, 74 Ong et al 75 and Ozmert et al 76 were not specifically on children with asthma as children with other forms of allergy were included. The findings in these studies may also have been affected by geographical and socio-economic differences in the areas where the studies were done as well as differences in the socio-economic classification tools used. xxvi
Intelligence Ability
Intelligence, measured as the Intelligence Quotient (IQ), is one of the important prognostic variables in the academic performance of a child74 and many factors including chronic diseases may impact upon it.77 IQ scores, as has been suggested may be an appropriate guide in the proper placement of school children at the beginning of their education.78 Children with borderline intelligence (IQ 68-83) or mental sub-normality, irrespective of the etiology, are known to present with poor school performance.79 Studies80, 81 on children with SCA have reported a significant correlation between IQ and academic performance. Chodorkoff and Whitten 80 in their study among children with SCA, found a significant correlation between IQ and school grade level placement. Swift and colleagues81 also reported academic achievement to be commensurate with measured intellectual ability in children with SCA.
A limited number of studies have investigated the IQ score of children with asthma. Javad et al 77 in a comparative study of the overall IQ scores of asthmatics and healthy children found that there were no significant differences in the overall scores and in the scores of males and females.
Similar findings were also reported by Daramola et al 82 among children with asthma.
Instruments for Assessing Academic Performance
Academic performance can be measured using attainment and achievement tools.83 Academic attainment tools, which include the school examination report and the school grade level placement, are direct measurements of school performance that are partially independent of formal testing situations.10 The academic achievement tools, on the other hand, are psychometric and standardized tests of academic skills frequently used as outcome measures to assess a child’s
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learning in school.74 Academic achievement tools include the Wide Range Achievement Test
(WRAT), Peabody Individual Achievement Test, Woodcock–Johnson Tests of Achievement,
Missouri Assessment Test and the Palmetto Achievement Challenge Test, which are curriculum- based tests assessing the child’s performance in areas such as reading, spelling, written language and mathematics.74 The academic attainment and achievement tools are advisably used in combination to provide a more complete assessment of the academic performance of an individual.83,84
The school examination report, an example of academic attainment measure 23, 25, 26 involves the use of the session’s aggregate score and scores in core specific subjects like Mathematics,
English Language, Sciences and Social Studies. It has been used in studies done in our environment.23, 25, 26 The schools examination report is easy to administer and even though it is not standardized for use in our environment, this is made up for by providing study controls.23, 25,
26 A score of less than 50% represents poor academic performance.23, 25, 26 It has the advantage of removing observer’s cultural biases since children of school age especially in primary classes are taught by the same teacher with the same syllabus. However, varying standards between teachers and schools and differences in schooling system may not allow for extrapolation of the results.
The Woodcock-Johnson test, which is an academic achievement tool, is used for children between 4 years and adulthood. In it, the broad mathematics and reading skill clusters are administered and age-adjusted standard scores calculated.85 Poor academic performance in the
Woodcock-Johnson test is defined by a performance rating of less than or equal to 1.5 standard deviation below age expectation on either broad reading or mathematics measures.85 The advantage of academic achievement tools is that they are standardized, hence reproducible.
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However, they are culture specific and some are cumbersome to administer and assess. Also, none of them has been validated for use in Nigeria.
Instruments for assessing Intelligence Quotient (IQ)
Academic performance also entails assessment of Intelligence Quotient (IQ) which can be done using the Stanford-Binet test of intelligence, Wechsler Intelligent Scale for Children (WISC) and the Draw-A-Person-Test (DAPT). 86, 87The Stanford-Binet Intelligence Scale assesses intelligence in children and adults aged 2-23 years and it tests intelligence across four areas- verbal reasoning, quantitative reasoning, visual reasoning and short term memory. 86 Its main drawback is that it relies heavily on verbal items.86 WISC has separate verbal and performance
IQ tests86 and is designed for subjects who are 6-16 years of age. It assesses the child’s intelligence in a more complete manner, addressing the drawbacks of the Stanford–Binet scale.
However, the WISC is long, requires two sittings and should be adapted to the country’s population before being used.74 Both the Stanford-Binet and the WISC tests have not been validated for use in our environment.
The Draw-A-Person-Test (DAPT) is non-verbal and can be administered to people of diverse culture and with linguistic barriers.87It can be scored by any physician who follows the rules, 87 is appealing to children88 and has been standardized and validated for use in Nigerian children.89 In the DAPT there are 52 criteria for scoring. The total number of points scored is the Draw-A-
Person-Point (DAPP). The DAPT has been shown to demonstrate a high correlation with the
Stanford-Binet and the WISC tests.89 Children below 4 years of age are unable to draw identifiable objects/figures because they lack the conception of order implying that they cannot draw any meaningful figure before 4 years of age.90, 91 In the DAPT, three points are added to
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compensate for the starting point of 4 years in order to obtain the calculated Draw-A-Person-Age
(DAPA).90, 91 A child is classified as normal if the Draw-A-Person-Quotient (DAPQ) is average for his age.89, 90, 91 A score <1SD or <75% of average score for age is regarded as mental dullness while a score 2SD lower than the age average is regarded as mental deficiency. 89, 90
AIMS AND OBJECTIVES
Research question
Do children with asthma perform poorer academically than non-asthmatic children?
What factors may affect academic performance of children with asthma?
Hypothesis
H0 - academic performance of children with asthma is not different from that of non-asthmatic children.
H1- children without asthma perform better academically that those with asthma
General Objective
To determine the academic performance of primary school children with asthma attending the
University of Nigeria Teaching Hospital, Ituku/Ozalla, Enugu State and the factors affecting it.
Specific Objectives
1. To determine the academic performance of primary school children with asthma.
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2. To determine the relationship between academic performance and asthma control.
3. To determine the relationship between academic performance and school absence.
4. To determine the relationship between academic performance and IQ.
5. To determine the relationship between academic performance and socio-economic status
of the families.
METHODOLOGY
Study Design
This was a cross-sectional, hospital- and school-based descriptive study.
Study Area
The study was carried out at the University of Nigeria Teaching Hospital (UNTH), Ituku/Ozalla,
Enugu State. The Subjects and Controls were recruited from among children resident in Enugu metropolis. Enugu is the capital of Enugu State. Its suburbs include Ituku and Ozalla communities which are about 20km from the town and are the host communities to the hospital.
Enugu is a major administrative, educational and trading centre, with coal as her most abundant natural resource. Enugu is inhabited by people from diverse walks of life and of all socioeconomic classes. The ethnic groups are mostly of the Igbo speaking tribe.
Study site
The University of Nigeria Teaching Hospital Ituku/Ozalla, Enugu State and the primary schools in Enugu metropolis were the sites for the study. The UNTH offers primary, secondary and, importantly, tertiary healthcare services to persons of all social classes and is the referral centre for the populations of the former eastern Nigeria and parts of Benue and Kogi States. It has
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specialist doctors and trains healthcare manpower with equipped clinics, wards, emergency units and laboratories particularly in the four broad clinical areas of medical practice- paediatrics, obstetrics and gynaecology, medicine and surgery.
The paediatric asthma clinic of the UNTH, Ituku/Ozalla holds every Tuesday morning with four doctors and three nurses attending to an average of 25 persons, including five new cases per week. The paediatric asthma clinic from the hospital records attends to an average of 304 patients per year, of which 148 patients (48.7%) are children aged 5-11 years.
Study Population
The study population comprised of school children with asthma (subjects) living in Enugu metropolis. The control population (children without asthma) was healthy classmates. The choice of classmates as controls was informed by the need to remove school-related bias and to control for class grade as suggested by Richard and Burlew.92
Sample Size The minimum sample size for the study was determining using the formula for sample size calculation93 that when the study population is >10,000: n = z 2 p q d2 where n = sample size z = z score at 95% confidence limit (1.96) p = estimated prevalence when prevalence of poor academic performance in children with asthma is not known = 0.50 q = 1.0 – p = 0.5 d = degree of accuracy at 95% confidence limit (0.05)
n = 1.962 x 0.5 x 0.5 0.052 = 384
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and when study population is <10,000, nf = n 1+ n N where nf = final sample size
n = sample size when study population is >10,000
N = study population size (number of school-aged asthmatics attending the asthma clinic)
= 148
nf = 384 1 + 384 148 = 107
Sample size allowing for 10% attrition = 120
The total number of children with a diagnosis of asthma enrolled into the study was 120. The age-, sex- and social class-matched controls were also 120. The total number of study participants was therefore 240.
Inclusion Criteria:
1. Children aged 5-11 years, attending primary school in Enugu metropolis.
2. Asthma diagnosed by a doctor.94, 95
3. Attendance in the same school for at least one session before study enrolment.
4. Attendance at the asthma clinic for at least 12months.
5. Consent for the study given by care-giver.
Exclusion Criteria:
1. Out of school children.
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2. Age less than five years or more than eleven years of.
3. Children with other chronic diseases like sickle cell disease, diabetes mellitus, tuberculosis,
congenital heart diseases or with history of neurologic illness like seizure disorders and
cerebral palsy. These were excluded because the disorders are known to affect academic
performance, hence the independent effect of asthma may be difficult to determine.96
4. Children attending school outside Enugu metropolis
5. Attendance of the present primary school for less than one session before enrolment
6. Refusal of consent by care-giver.
7. Asthmatic children with incomplete data, since some of the information were obtained
from the case notes.
Control group
The child next to the asthma patient in the class register was selected as control if he/she met the following criteria:
1. Of same sex, age (within 6 months) and socio-economic class as the child with asthma.
2. Has been in the same primary school and class as the asthmatic child for at least one
session before study enrolment.
3. Does not have any of the exclusion criteria as listed for the subjects
If the next child to the asthmatic in the class register did not meet the criteria, the most suitable child without asthma down the register who meets the criteria was chosen as control.
Selection and evaluation of the subjects
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The study was carried out in two phases. Firstly the subjects were enrolled from the clinic while their controls were enrolled from the corresponding schools. The subjects and controls were matched for age, sex and socio-economic class. The choice of classmates as controls was informed by the need to remove school-related bias. The consent of the caregivers of both groups as well as the school authorities (Education Board, local school head teachers and class teachers) was obtained.
At the asthma clinic
On presentation at the clinic, the caregiver and the child with asthma were informed of the study and written informed consent (Appendix I) obtained from the caregiver. Before enrollment, in order to ascertain eligibility, the asthmatic child’s socio-demographic data was obtained and the child subsequently assessed clinically for chronic and debilitating medical conditions such as heart disease, seizure disorders and cerebral palsy that are known to affect academic performance independently. 96 The information obtained was recorded in the proforma (Appendix II).
Children who meet the inclusion criteria were enrolled consecutively till the sample size was reached while those excluded were scheduled for consultation. The socio-economic status of the
Subjects was determined using the method described by Oyedeji (Appendix III).97 The level of asthma control was ascertained using the Childhood Asthma Control Test (C-ACT)49 (Appendix
IV). The subjects were then given a sheet of paper and pencil and left alone with as much time as they needed with the instruction to draw a person.89, 90 The IQ of the subjects was calculated using the validated Ziler criteria 89 and the table of DAPQ by Ebigbo and Izuora89 (Appendix VI and VII).
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The child with asthma was subsequently reviewed, complaints attended to and future clinic appointment given. However, children with acute exacerbation of asthma were first managed in the Children Emergency Room of UNTH before evaluation for the study.
In the schools
The clearance letter from the Ministry of Education (Appendix V) was used to obtain permission for the study at the various schools. At the school/class of each enrolled asthmatic child, the head/class teacher was informed of the study in order to access the child with asthma (subject) and to enroll the child without asthma (control). Also the need to obtain the information with regards to the children’s school performance was explained.
With the help of the class teacher, the non-asthmatic child, next to the study subject in the class register, who was of the same age and sex as the child with asthma was recruited. The recruited non-asthmatic child was then informed of the study and given the consent form for the caregiver to fill (Appendix I). The consent form was retrieved on a subsequent visit to the school. The non- asthmatic child whose caregivers gave consent was then interviewed for eligibility for the study and the socio-economic status determined as described for the subjects (Appendix III). The selected control was then enrolled and the questionnaire (Appendix II) administered.
The control was also given a sheet of paper and pencil and left alone with as much time as needed with the instruction to draw a person and was scored using the validated Ziler criteria by
Ebigbo and Izuora.89
With the help of the class teacher, using the pupils’ academic records, information on class position, overall score and scores in key subjects (Mathematics, English, Social Studies and
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Sciences) for the subjects and controls was obtained and recorded (Appendix VIII). The average overall percentage score for each child in the three terminal examinations in the 2012/2013 academic year was documented and was used as an index of the general/overall academic performance.23, 25 The average of the three scores from the three academic terms for each child in four selected key subjects was used as the index of specific academic performance.23, 25
From the class attendance register, each child’s total number of days of absence for the entire academic year was obtained. School absence was classified as described by Weitzman and colleagues. 68 Any information not properly filled out or not filled at all on the proforma was requested for directly from the caregiver through personal and or phone contacts.
PARAMETERS EVALUATED
Academic Performance
Children who scored <50% overall or in a specific academic skill were considered as having poor academic performance overall or with respect to that specific academic skill/key subject whereas scores ≥50% (average 50-74% and high scores ≥75%) were considered good academic performance.23, 25 Good academic performance was further classified into average scores (50-
74%) and high scores (≥ 75%).23, 25
Intelligence Quotient
Intelligent quotient (IQ) was assessed using the Draw-A-Person Test (DAPT). 89 The total number of points scored is the Draw a Person Point (DAPP). DAPQ = DAPA/ Chronologic Age, where DAPA = (DAPP+ 3) / 4. The DAPQ score obtained was compared with the expected
DAPQ score for age and sex using the table for average DAPQ scores by Ebigbo89 (Appendix xxxvii
VII). A score of less than 75% for sex and age was regarded as mental dullness or backwardness.89
School absence
High school absence was taken as >12 school day’s absence and low school absence as 1 – 12 school days’ absence.68
Asthma control
This was assessed on the patient’s visit to the clinic using the Childhood Asthma Control Test
(C-ACT™) tool (Appendix IV).49 This C-ACT TM tool for children 4 to 11 years is made up of seven questions with a total score of 27 as the highest score obtainable. Each child, as much as possible, was allowed to answer the first four questions unaided while the care-giver answered the remaining three. A score of 19 and below signified poor control while scores above 19 indicate good control.44, 58
Socio-economic class
This was determined using the occupation and educational attainment of the caregiver to get the socio-economic class as described by Oyedeji (Appendix III).97 The socio-economic class was obtained by finding the mean score for the parents educational attainment and occupation rounded off to the nearest whole number. Where any of the parents were dead, the social class of the child was assessed using that of the living parent. Socio-economic class I represent the highest socio-economic class and class V the lowest.
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ETHICAL CLEARANCE AND CONSENT
Ethical approval was obtained from the Health Research Ethics Committee of the UNTH
(Appendix IX). Clearance was obtained from the Enugu State Ministry of Education as it entailed visitation of schools and use of school registers (Appendix V). Written informed consent was obtained from the caregiver (Appendix I) and every history and physical examination was done with a chaperone present (nurse in the hospital and class teacher in the schools). Information gathered from participants was coded and treated with utmost confidentiality.
DATA MANAGEMENT AND STATISTICAL ANALYSIS
Information obtained from the participants was recorded in the questionnaire/proforma and subsequently transferred into the data editor of Statistical Package for Social Sciences (SPSS) software for Windows® version 19.0 (IBM Inc Chicago Illinois USA, 2011) for analysis.
Descriptive statistics such as mean ± (SD) and median were obtained for continuous variables while categorical variables were summarized using frequencies and percentages. The comparison of the means of IQ which was normally distributed was done using Student’s t-test and ANOVA while other variables that were not normally distributed (Academic performance, Socio- economic class and school absence) were compared using the Mann-Whitney U test. The significance of the association between categorical variables was determined using chi-square.
Tests of relationships were also done using Pearson and Spearman’s rho correlation where
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appropriate and also multiple linear regression analysis. All the tests were taken as significant at p < 0.05. Results are presented in tables, scatter plots and graphs.
RESULTS
Socio-demographic characteristics of the Subjects and Controls
A total of 240 children comprising 120 subjects and 120 controls were enrolled in the study.
They were selected from 105 primary schools within Enugu metropolis. Of the 105 primary schools, 60 were public schools from where 77 subjects and controls each were enrolled while 45 were private schools from where 43 subjects and controls were enrolled.
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Table I shows the age and sex distribution of the study participants. There were 81 (67.5%) males and 39 (32.5%) females (male: female ratio 2.1:1) in each group. The age range was 5 to
11 years and the overall mean age ± SD was 8.20 ± 1.92 years. Sixty-nine (57.5%) of the 120 subjects and controls were in early primary school age (5-8years) while fifty-one (42.5%) were in late primary school age (9–11 years). Out of the 69 subjects and controls in early school age,
45 (65.2%) were male and 24 (34.8%) females while 36 (70.6%) of the 51 subjects and controls in late school age were male and 15 (29.4%) females ( 2 = 0.39; p < 0.535). The mean age ± SD for males and females was 8.07 ± 1.73 and 8.47 ± 2.26 years, respectively. The difference in the mean age of males and females was not statistically significant (t = 1.47, p = 0.143).
Thirty (25%) of the subjects were from socio-economic class I and sixty (50%) from socio- economic class II while only twelve (10%) were from socio-economic class III and eighteen
(15%) from class IV. No subject or control studied was from socio-economic class V.
Thirty out of the 120 subjects (25%) had poor asthma control while 90 (75%) had good asthma control.
The mean IQ scores for subjects and controls were 123.28 ± 21.45 and 118.41 ± 19.87, respectively. The difference was not statistically significant (t = 1.83; p = 0.069).
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Table I: Age and sex distribution of the subjects and controls.
subjects controls Age (years) Male (%) Female (%) Male (%) Female (%) 5 – 8 45 (55.6) 24 (61.5) 45 (55.6) 24 (61.5)
9 – 11 36 (44.4) 15 (38.5) 36 (44.4) 15 (38.5)
Total 81 (100.0) 39 (100.0) 81 (100.0) 39 (100.0)
2 = 0.39, d.f = 1, p < 0.535
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Academic performance of the subjects and controls
The median (range) overall academic scores for the subjects and controls as shown in Table II were 79.04% (36.08% - 99.57%) and 80.01% (50.65% - 97.47%), respectively. The difference in the median overall academic scores for the subjects and controls was not statistically significant
(U = 6804, p = 0.461). There was also no statistically significant difference between subjects and controls in selected key subjects.
The median overall scores for male subjects and controls are shown in Table III and that for female subjects and controls in Table IV. There was a statistically significant difference in median overall academic scores between male subjects and controls (p = 0.017) (Table III) but not between female subjects and controls (p = 0.137) (Table IV). There was also a statistically significance difference in median scores for mathematics (p = 0.008) and social studies (p =
0.005) between male subjects and controls (Table III) and for English between female subjects and controls (p = 0.001) (Table IV). The difference between male subjects and controls in median scores for English (p = 0.625) (Table III) and between female subjects and controls in median scores for mathematics (p = 0.137), social studies (p = 0.892) and sciences (p = 0.857)
(Table IV) were not significant.
Tables Va and Vb show the comparison of overall academic performance and performance in specific subjects between male and female Subjects while table VI a and VI b show the same for controls. There was no statistically significant difference in the overall academic performance between male and female subjects ( 2 = 0.89; d.f = 2; p = 0.642) but there was a statistically significant difference in the overall academic performance between male and female controls ( 2
= 17.38; d.f = 1; p < 0.001). While female asthmatics did not perform significantly better than xliv
male asthmatics in all the four key subjects (Mathematics (p =0.181), Social studies (p = 0.245),
Sciences (p = 0.077) and English ( p = 0.596 )); female controls performed better than male control in all four key subjects (English language, Mathematics and Social studies (p <0.001) and
Sciences (p = 0.002)).
The age-specific comparison of median overall academic scores between the subjects and controls is shown in Table VII. There were statistically significant differences in the median overall academic scores at ages 7 (p = 0.045), 9 (p = 0.015) and 11 (p = 0.009) years. The differences at 6 and 10 years approached statistical significance. The median score of subjects was higher than that of controls at 6, 7 and 9 years and lower at 10 and 11 years. There was a statistically significant weak negative correlation (Pearson’s) between age and median overall scores in the subjects (r = - 0.467, p < 0.001)). The correlation among the controls was not statistically significant (r = - 0.146, p = 0.112).
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Table II: Comparison of median overall and specific subjects scores of study subjects and controls
subjects (n = 120) controls (n = 120 Mann- P – value Whitney Subjects Median (Mean rank) Median (Mean rank) U
Overall score 79.04 (123.80) 80.01 (117.20) 6804.00 0.461
Mathematics 78.67 (125.23) 71.00 (115.78) 6633.00 0.292
English 78.67 (113.90) 83.17 (127.10) 6408.00 0.141
Social studies 83.00 (129.24) 82.17 (111.76) 6151.50 0.051
Science 79.34 (121.55) 81.33 (119.45) 7074.00 0.815
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Table III: Comparison of median overall and specific subjects scores of male subjects and controls
subjects (n = 81) controls (n = 81) Mann- p-value Whitney U Subjects Median (Mean rank) Median (Mean rank)
Overall score 78.11 (90.33) 70.35 (72.67) 2565.00 0.017
Mathematics 74.33 (91.33) 64.74 (71.67) 2484.00 0.008
English 79.00 (84.78) 70.00 (78.22) 3015.00 0.374
Social studies 83.00 (91.94) 68.50 (71.06) 2434.50 0.005
Science 79.00 (83.28) 73.33 (79.72) 3136.50 0.629
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Table IV: Comparison of median overall and specific subjects scores of female subjects and controls
subjects (n = 39) controls (n = 39) Mann- P -value Whitney Subjects Median (Mean rank) Median (Mean rank) U
Overall score 84.00 (35.69) 90.33 (43.31) 612.00 0.137
Mathematics 84.81 (35.69) 89.33 (43.31) 612.00 0.137
English 76.67 (30.27) 94.00 (47.73) 400.50 < 0.001
Social studies 91.67 (39.15) 85.00 (39.85) 747.00 0.892
Science 90.00 (39.04) 90.00 (39.96) 742.50 0.857
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Table Va: Comparison of academic performance of male and female subjects
Academic Performance Poor Average Good Total Groups n (%) n (%) n (%) Male 3 (3.7) 33 (40.7) 45 (55.6) 81 (100.0)
Female 3 (7.7) 15 (38.5) 21 (53.8) 39 (100.0)
Total 6 (5.0) 48 (40.0) 66 (55.0) 120 (100.0)
2 = 0.89; d.f = 2; p = 0.642
Table Vb: Comparison of median overall and specific subject scores of male and female subjects.
Male (n = 81) Female (n = 39) Mann- p-value Whitney U Subjects Median (Mean rank) Median (Mean rank)
Overall score 78.11 (90.33) 84.00 (35.69) 1474.50 0.556
Mathematics 74.33 (91.33) 84.81 (35.69) 1341.00 0.181
English 79.00 (84.78) 76.67 (30.27) 1485.00 0.596
Social studies 83.00 (91.94) 91.67 (39.15) 1372.50 0.245
Science 79.00 (83.28) 90.00 (39.04) 1264.50 0.077
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Table VI a: Comparison of academic performance of male and female controls
Academic Performance Poor Average Good Total Groups n (%) n (%) n (%) n (%) Male 0 (0.0) 45 (55.6) 36 (44.4) 81 (100.0)
Female 0 (0.0) 6 (15.4) 33 (84.6) 39 (100.0)
Total 0 (0.0) 51 (42.5) 69 (57.5) 120 (100.0)
2 = 17.38; d.f = 1; p < 0.001
Table VI b: Comparison of median overall and specific subject scores of male and female Controls
Male (n = 81) Female (n = 39) Mann- p-value Whitney U Subjects Median (Mean rank) Median (Mean rank)
Overall score 70.35 (72.67) 90.33 (43.31) 772.00 < 0.001
Mathematics 64.74 (71.67) 89.33 (43.31) 931.50 < 0.001
English 70.00 (78.22) 94.00 (47.73) 859.50 < 0.001
Social studies 68.50 (71.06) 85.00 (39.85) 936.00 < 0.001
Science 73.33 (79.72) 90.00 (39.96) 1039.50 0.002
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Table VII: Age specific comparison of median overall scores between subjects and controls
subjects controls Mann- p -value Whitney U Age (years) Median (Mean rank) Median (Mean rank)
5 80.63 (18.50) 82.34 (18.50) 162.00 1.000
6 99.10 (5.00) 91.49 (2.00) 0.00 0.050
7 87.68 (22.00) 82.38 (15.00) 99.00 0.045
8 84.35 (31.70) 86.39 (29.30) 414.00 0.594
9 72.54 (29.38) 59.88 (19.63) 171.00 0.015
10 91.47 (2.00) 97.47 (5.00) 0.00 0.050
11 65.00 (19.25) 71.83 (29.75) 162.00 0.009
`
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Relationship between academic performance and asthma control among the subjects.
The median (range) overall academic score for children with poor asthma control was 79.96%
(36.00% - 93.57%) while that of those with good control was 78.11% (37% - 99.57%). The difference in the median overall academic score for children with poor asthma control and good control was not statistically significant (U= 1235, p = 0.486). The mean ± SD DAPQ scores for children with poor asthma control was 122.91±18.54 and children with good control 123.41±
22.54. The difference was not statistically significant (p = 0.215).
The relationship between asthma control and academic performance among the subjects is shown in Table VIII. Overall, 30 subjects (25%) had poor control and academic performance of six of them (5%) was poor. There was no significant relationship between asthma control and academic performance ( 2 = 3.18; d.f = 2; p = 0.204).
The age specific comparison of academic performance of subjects is shown in table IX in relation to asthma control. Children with poor asthma control had significantly lower median overall academic scores at ages 9 (P = 0.032) and 11years (p = 0.015) and higher mean scores at
5years (p = 0.002). Comparisons could not be made at 6and 10 years of age because none of the children at these ages had poor control. There was a statistically significant negative correlation
(Pearson’s) between age and median overall score in subjects with poor (r = -0.839, p <0.001) and good (r = - 0.341, p = 0.001) asthma control.
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Table VIII: Comparison of academic performance and asthma control of subjects
Academic Performance Poor Average Good Total Asthma control n (%) n (%) n (%) n (%) Good 3 (3.3) 39 (43.3) 48 (53.3) 90 (100.0)
Poor 3 (10.0) 9 (30.0) 18 (60.0) 30 (100.0)
Total 6 (5.0) 48 (40.0) 66 (55.0) 120 (100.0)
2 = 3.18; d.f = 2; p = 0.204
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Table IX: Age specific comparison of academic performance and asthma control of subjects
Asthma control
Poor (n = 30) Good (n = 90) Mann- p -value Whitney U Age (years) Median (Mean rank) Median (Mean rank)
5 89.12 (15.00) 78.11 (6.75) 3.00 0.002
6 NA 99.57 (2.00) NA NA
7 82.28 (6.50) 92.84 (11.00) 18.00 0.089
8 83.94 (12.42) 86.62 (16.27) 53.50 0.336
9 71.28 (7.17) 73.96 (14.28) 22.00 0.032
10 NA 91.00 (2.00) NA NA
11 49.39 (6.50) 68.31 (14.50) 18.00 0.015
NA = Not Available
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Relationship between academic performance and school attendance among the subjects and controls.
During the academic session under study, the median number (range) of days of absence from school for the entire study population was 6 (1 - 41) days. The median number (range) of days absent from school was 9 (1 - 29) days for the subjects and 3 (1 - 41) days for the controls. The difference was highly statistically significant (U= 5103, p < 0.001). The median number (range) of days of school absence of the subjects with poor asthma control (8 (1 - 29) days) was not significantly different from that of those with good control (7 (1 – 41) days) (U = 1259.50, p =
0.581).
Of the 120 subjects and controls studied, only 18 subjects (15%) did not miss any school day compared to 42 (35%) of controls. Among the 102 subjects who missed school days, thirty-six
(35.3%) had high school absence while 66 (64.7%) had low school absence. Among the 78 controls who missed school days, twenty- one (26.9%) had high school absence and 57 (73.1%) had low school absence. The prevalence of high school absence was significantly higher in subjects compared to controls ( 2 = 5.18, p = 0.023).
Out of the 69 male subjects that missed school, 21(30.4%) had high absence and 48 (69.6%) had low absence while out of the 51 male controls that missed school, 21(41.2%) had high absence and 30 (58.8 %) had low absence. The difference in the prevalence of high school absence in male subjects compared to male controls was not statistically significant ( 2= 1.49, p = 0.223).
Out of the 33 females subjects that missed school, 15 (45.5%) had high absence and 18 (54.5%) had low school absence while all the 27 (100.0%) female controls that missed school had low absence. The difference in the prevalence of high school absence in female subjects compared to female controls was statistically significant ( 2 =16.36, p < 0.001). lv
Table X compares asthma control with school absence. From the table, 33(91.7%) out of the 36 subjects with high school absence had poor asthma control while the remaining 3 (8.3%) had good asthma control. The prevalence of high school absence among subjects with poor asthma was higher compared to those with good asthma control and this difference was highly statistically significant ( 2 = 14.67; d.f = 1; p < 0.001).
Forty eight subjects (40%) had a history of hospital admission which ranged from 1 to 5 days and 48 (40%) had emergency room visits of 1-5 times in the previous one year. Thirty-five percent of all the subjects had acute asthma attacks as the only reason for hospital admission.
Majority (77.8%) of the asthmatics who had hospital admissions had an average hospital stay of one to three days before discharge. High school absence in the subjects was significantly associated with hospital admissions and emergency room visits ( 2 = 16.08; d.f = 1; p < 0.001).
The comparison of academic performance and school absence in subjects and controls is as shown on Table XI. Among the subjects and controls, six (5%) subjects had poor academic performance while none of the controls had poor academic performance. These six subjects with poor academic performance however had low school absence and none of the subjects or controls with high school absence had poor academic performance. The number of controls who had average and good academic performance was higher than that of subjects. However there was no significant association between academic performance and school absence in both subjects ( 2 = 3.92, d.f = 2, p = 0.141) and controls ( 2 = 0.59, d.f = 1, p = 0.444).
Table XII compared the age specific differences in median number of days of absence from school between subjects and control. The subjects at ages 5, 6 10 and 11years had more days of absence from school compared to controls (ages 5 (p < 0.001), 6 and 10 (p = 0.025) and 11 (p <
0.001). lvi
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Table X: Comparison of asthma control and school absence amongst subjects
Asthma control Poor Good Total No. of days absent n (%) n (%) n (%) Low absence 36 (54.5) 30 (45.5) 66 (100.0)
High absence 33 (91.7) 3 (8.3) 36 (100.0)
Total 69 (67.6) 33 (32.4) 102 (100.0)
2 = 14.67; d.f = 1; p < 0.001
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Table XI: Association between academic performance and number of days absent of subjects and controls
Academic performance of subjects Academic performance of controls School Absence Poor Average Good Poor Average Good n (%) n (%) n (%) n (%) n (%) n (%) Low 6 (9.1) 21 (31.8) 39 (59.1) 0 (0.0) 27 (47.4) 30 (52.6)
High 0 (0.0) 15 (41.7) 21 (58.3) 0 (0.0) 12 (57.1) 9 (42.9)
Total 6 (5.9) 36 (35.3) 60 (58.8) 0 (0.0) 39 (50.0) 39 (50.0)
2/d.f / p value 3.92/2/0.141 0.59/1/0.444
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Table XII: Age specific comparison of school absence between subjects and controls.
Number of days of Absence
Age (years) subjects controls Mann- p -value Whitney U Median (Mean rank) Median (Mean rank)
5 12.00 (24.75) 5.500 (12.25) 49.50 < 0.001
6 6.00 (5.00) 0.00 (2.00) 0.01 0.025
7 6.50 (20.00) 2.00 (17.00) 135.00 0.372
8 6.50 (27.95) 10.00 (33.05) 373.50 0.255
9 8.00 (25.81) 6.500 (23.19) 256.50 0.512
10 3.00 (5.00) 0.00 (2.00) 0.02 0.025
11 12.50 (32.00) 0.000 (17.00) 108.00 < 0.001
Relationship between academic performance and DAPQ scores of subjects and controls.
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The overall mean ± SD and gender- related DAPQ scores of the subjects and controls are shown in Table XIII. There was no statistically significant difference between the subjects and controls in their overall mean DAPQ (t = 1.82, p = 0.069) and in mean DAPQ of male pupils (t = 0.05, p
= 0.963). Female subjects however had a higher mean DAPQ than female controls. The difference was highly statistically significant (t = 3.52, p = 0.001).
The age specific differences in mean IQ scores for subjects and controls are shown in Table XIV.
There were statistically significant differences between the subjects and controls in all the age groups except at 8 and 9 years of age. Mean IQ was found to differ significantly across the ages in both subjects (F = 7.46, p < 0.001) and controls (F = 14.41, p < 0.001). There was also a significant and negative correlation (Pearson’s) between age and mean DAPQ in both the subjects and controls (r = -0.377, p < 0.001; r = -0.492, p < 0.001 respectively.
Figures 1a and 1b are scatter plots showing the relationship between IQ and academic performance among the subjects and controls. There are increased cluster of points in an upward manner from left to right indicating a statistically significant correlation between academic performance and DAPQ in both the subjects (r= 0.213, p = 0.020) and controls (r= 0.318, p <
0.001) respectively.
Table XIII: Mean ± SD overall and gender-related DAPQ scores of subjects and control.
DAPQ Scores
Status subjects (n = 120) controls (n = 120) t-value p - value
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Mean ± SD Mean ± SD
Overall 123.28 ± 21.45 118.41 ± 19.87 1.826 0.069
Males 119.18 ± 21.24 119.33 ± 20.37 0.047 0.963
Females 131.80 ± 19.52 116.49 ± 18.89 3.521 0.001 t-value 3.128 0.734 p – value 0.002 0.464
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Table XIV: Age specific comparison of mean DAPQ scores of subjects and controls.
subjects controls
Age (years) N (%) Mean ± SD Mean ± SD t p-value
5 18 (15) 146.15 ± 30.24 127.21 ± 24.89 2.052 0.048
6 3 (2.5) 123.67 ± 0.15 120.60 ± 0.54 9.451 0.001
7 18 (15) 125.95 ± 12.93 140.02 ± 14.37 3.087 0.004
8 30 (25) 122.46 ± 19.03 122.59 ± 13.56 0.030 0.976
9 24 (20) 108.16 ± 13.09 104.24 ± 10.07 1.164 0.250
10 3 (2.5) 110.87 ± 0.64 122.54 ± 0.19 30.418 < 0.001
11 24 (20) 121.72 ± 16.66 103.75 ± 14.60 3.973 < 0.001
F- value 7.461 14.416
P value < 0.001 < 0.001
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Figure 1a: A scatter diagram showing the relationship between IQ and academic performance among subjects
Figure 1b: A scatter diagram showing the relationship between IQ and academic performance among controls.
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Relationship between academic performance and socio-economic status of subjects and controls.
Table XV shows the relationship between academic performance and socio-economic class of subjects and controls. Of the thirty subjects in class I, fifteen (50%) had average performance and the remaining fifteen (50%) had good academic performance while of the thirty controls in socio-economic class I, eighteen (60%) had average performance and 12 (40%) had good performance. Twelve (66.7%) of the eighteen subjects in socio-economic class IV had average performance and only three (16.7%) had good academic performance while only three (16.7%) of controls in socio-economic class IV had average academic performance and fifteen (83.3%) had good academic performance. No control had poor academic performance however six subjects had poor academic performance. While none of the subjects with poor academic performance were in socio-economic class I, three (50%) of subjects with poor academic performance were in socio-economic class IV. None of the study participants (subjects and controls) were in socio-economic class V. A significant association exists between academic performance and socio-economic class in both subjects ( 2 = 20.034, d.f = 6, p = 0.003) and control ( 2 = 18.926, d.f = 3, p < 0.001). Academic performance has a significant but weak correlation (Spearman’s) with socioeconomic class among the subjects (r = 0.194; p = 0.034) but not among controls (r = - 0.122; p = 0.185).
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Table XV: Relationship between academic performance and socio-economic class of subjects and controls
Academic Performance of subjects Academic Performance of controls Poor Average Good Poor Average Good Socio-economic class n (%) n (%) n (%) n (%) n (%) n (%) Class1 0 (0.0) 15 (50.0) 15 (50.0) 0 (0.0) 18 (60.0) 12 (40.0)
Class2 3 (5.0) 18 (30.0) 39 (65.0) 0 (0.0) 30 (50.0) 30 (50.0)
Class 3 0 (0.0) 3 (25.0) 9 (75.0) 0 (0.0) 0 (0.0) 12 (100.0)
Class 4 3 (16.7) 12 (66.7) 3 (16.7) 0 (0.0) 3 (16.7) 15 (83.3)
Total 6 (5.0) 48 (40.0) 66 (55.0) 0 (0.0) 51 (42.5) 69 (57.5)
2/(d.f)/ p value 20.03/6/0.003 18.93/3/< 0.001
Multiple Linear regression analysis for predictors of academic performance in subjects and
controls lxvi
In the multiple regression results shown in Tables XVI and XVII, the coefficient of determination in both subjects and controls (R2 = 0.311, R2 = 0.192 respectively) indicate that less than half the variation in academic performance is explained by the model.
Among the subjects, asthma control had a significant positive effect on academic performance (B
= 1.080, p = 0.003), age had a significant negative effect on academic performance (B = -3.776, p < 0.001). However, socio-economic class, DAPQ and school absence did not have significant effect on academic performance.
Among the controls, socio-economic class and DAPQ had significant positive effect on academic performance (B = 3.580, p =0.007; B = 0.245, p =0.001 respectively), school absence had a significant negative effect on academic performance while age had no significant effect on academic performance.
Table XVI: Multiple linear regression result of predictors of academic performance in subjects
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Variables B p- value Age -3.776 <0.001 Socio-economic class 1.836 0.183 DAPQ 0.034 0.579 Asthma control 1.080 0.003 No. of days absent 0.148 0.394 R = 0.557; R2 = 0.311
Table XVII: Multiple linear regression result of predictors of academic performance in controls
Variables B P value
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Age -0.273 0.718
Socio-economic class 3.580 0.007 DAPQ 0.245 0.001 No. of days absent -0.354 0.024 R= 0.438; R2 = 0.192
lxix
DISCUSSION
In this study of aspects of academic performance and its determinants among primary school children with asthma, the overall academic performance of the subjects as well as in selected school subjects of children was comparable with that of age-, sex- and socio-economic class- matched controls. Prevalence of high school absence was more among the subjects. However high school absence was not significantly associated with poor academic outcome among subjects when compared to controls. Increased IQ and upper socio-economic status were associated with good academic performance among subjects. Asthma control had significant positive effect on academic performance of the subjects.
The finding of a male preponderance among the subjects is consistent with the reports from previous studies 21, 41, 42 that noted that males are more affected by asthma before puberty. The reason suggested was the smaller lung size in males in childhood which however becomes larger in adulthood.21 The male preponderance may also reflect preferential treatment, even in health matters, given to male children in our environment.26 The subjects in this study were recruited from the hospital.
Majority of the subjects belonged to socio-economic classes I and II and none of the subjects were in socio-economic class V. This is in keeping with earlier reports 4, 72 that noted asthma to be one of the few diseases that are more common in the higher socio-economic classes. The reason could be due to life style encounters like early use of formula feeds, canned foods with additives and other social factors that are more common among people of higher socio-economic class compared to those in the lower socio-economic classes and can predispose to airway hypersensitivity. It could also indicate that more parents in the socio-economic classes I and II,
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compared to those in the socio-economic classes III and IV, avail themselves of the specialized services offered by the teaching hospital.26
In this study, the overall academic performance of subjects did not differ from those of controls.
This corroborates the findings of earlier studies.8, 13, 60 This could be because majority of the subjects in this study had good asthma control which may have masked the effect of asthma on academic performance. However Fowler et al 15 working in the USA reported a greater likelihood of poor academic performance among children with asthma compared with healthy children. This was an epidemiological survey on children using the grade system of education which did not exclude other chronic conditions known to affect academic performance. In contrast to the study by Fowler et al, 15 this study excluded children with chronic diseases such as SCA, Epilepsy and cerebral palsy that are known to affect academic performance of children.
Other confounding variables like socio-economic class were also accounted for. Also in contrast to this study, the level of asthma control was not considered in the study by Fowler et al.15
Studies on academic performance of children with other chronic diseases such as sickle cell anaemia23 and epilepsy26 done in the same study environment using similar study design as used in this study, found that overall academic performance of these children were not significantly different from the age-, sex- and socio-economic class- matched classmates. The reason for this finding could be the similarity in the IQ and socio-economic class of the subject and control groups since these were the factors that were noted to be associated with academic performance of these children. In addition these studies, similar to this study, are hospital- based using children who are accessing specialized care in the hospital and this could have masked the effect of the disease on their academic performance compared to their healthy controls.
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There was also no difference in academic performance between subjects and controls with regards to selected specific subjects. This is in agreement with the work by Gutstadt et al 13 and is also similar to the report from studies on other chronic diseases like SCA and epilepsy.23, 25, 79
However; this finding is at variance with that of Krenitsky-Korn who reported that children with asthma scored significantly lower in mathematics when compared with children without asthma.
While Krenitsky-Korn’s work was based on interviewer reported responses on performance in mathematics only, this study more objectively obtained and used the scores of the children in mathematics as well as in three additional key subjects (English, Sciences, Social studies) over an academic year
Differences were noted between subjects and controls in overall academic performance and performance in selected key subjects. Male subjects had better academic performance overall as well as in mathematics and social studies compared to male controls. This differs from the report by Krenitsky-Korn 12 and Gutstadt et al 13Also female subjects performed poorer than their female Controls in English. The reason for these differences is unclear. However, the better academic performance noticed among male asthmatics compared to male controls could be because these male asthmatics reduce activities that may result in asthma attacks and channel their time and energy to reading and other academic activities. The significantly higher proportion of males compared to females in the study population may also have influenced these findings.
Male subjects compared favorably well with female subjects in overall performance and in the four specific subjects but male controls performed significantly poorly compared to female controls The reason for these gender differences in academic performance between male and
lxxii
female subjects and controls is unclear. Earlier works had suggested that males perform better than females especially in mathematics and science and this was linked to differential development in the cerebral hemispheres of males and females during intra-uterine life caused by circulating perinatal hormones, 98 social factors 99 and genetics. 100, 101, 102 More recently the reverse is believed to be the case as female children are reported to perform better than their male colleagues in virtually all subjects including Mathematics and Sciences that were previously thought to be within the male domain.103 They suggested that social and cultural factors could be among several possible explanations for this new trend and that parents may assume boys are better at mathematics and science so they might encourage girls to put more effort into their studies, which could lead to the slight advantage girls have in all courses. 103
Gender differences in learning style were also suggested as another possibility as girls tend to study in order to understand the materials, whereas boys emphasize performance.103 The high proportion of subjects with good asthma control in a subject population that is largely male may also have contributed to the lack of significant difference in academic performance between male and female subjects compared to the finding among the controls in this study.
In this study, School absence was significantly higher among the subjects. This finding is similar to previous reports on asthma 5, 12, 13, 15, 60-63 and other chronic ill-health. 5, 77 The reason could be the frequent routine follow-up visits and recurrent attacks resulting in frequent hospitalization found among the subjects in this study which is also in keeping with the reports from some earlier studies.4-10, 57 Asthma control status was related to high school absence as prevalence of high school absence was significantly higher in children with poor asthma control compared to those with good asthma control. This corroborates the finding by Moonie et al 6 and Diette and colleagues.11The reason for increased school absence among the subjects with poor asthma lxxiii
control compared to those with good asthma control could be the frequent hospital visits by these children as was found in this study which could take them out of school more than those with good asthma control. However, Diette et al 11 in his study suggested that the reason for increased school absence in children with poor asthma control was night awakening due to occurrence of asthma symptoms at night which is more in children with poor asthma control.
Although there was higher school absence among the subjects, this did not affect their academic performance. This is in agreement with the finding of Moonie et al 6 who also did not observe any difference academically between children with asthma and those without except in children with persistent asthma who also had more days of absence from school. The reason for the lack of significant effect of school absence on academic performance of the subjects could be because a greater percentage of them were from the higher socio-economic class as children in the higher socio- economic class are known to perform better academically compared to those in lower socio-economic class who are faced with poor motivation, unsatisfactory home environment and neglect, poor housing and nutrition.74, 75, 76 Therefore the subjects in this study who are largely from the higher socio-economic class could have enjoyed good parental motivation coupled with extra lessons at home and school which enabled them to make up academically. In addition, these subjects may have channeled their energy and time away from exercises and other activities that could trigger asthma attacks towards reading and other academic work.
Weitzman et al 68 however, noted a negative impact of school absence on academic performance which differs from the finding in this study. Differences in study design and environment between this study and that of Weitzman et al 68 may be responsible. While the study by
Weitzman et al 68 was a community-based work in which they studied school absence and its
lxxiv
impact on their academic performance of children in the United State of America, this study looked specifically at school absence and academic performance amongst Nigerian children with asthma and compared them with matched classmates without asthma. Similar finding to this study was also reported by Ibekwe et al 23 and Ezenwosu et al 26 among children with epilepsy and SCA respectively.
All the children in this study had IQs within the normal range for age and sex and there was no difference in IQ between subjects and controls. This is consistent with the findings of Daramola and colleagues82 at Ibadan, Nigeria as well as Javad et al 77 in Iran. While this study used the
DAPT to assess IQ, Javad et al 77used WISC, and Daramola et al 82 in Ibadan, Nigeria used
SPM. The similarity in the findings from the studies by Javad et al 77and Daramola et al 82 with that of this study despite use of different IQ assessment tools and having been done in three different areas aligns with a report of high correlation between DAPT and other IQ assessment tests.89
There was no difference in mean IQ between male subjects and controls however; female subjects had a significantly higher mean IQ compared to their controls. While Javad et al 77 in his study reported that there was no significant difference in mean IQ in relation to gender,
Daramola and colleagues, 82 whose work was done in Nigeria as was this study, did not explore gender difference with respect to mean IQ score. The reason for the significantly higher IQ among female subjects compared to female controls is unknown.
A decline in mean IQ scores with age in both the subjects and controls was observed in this study. Although decline in IQ is known to occur over time as people age, such declines were mostly noted to occur in older age compared to the finding of this study except in children with
lxxv
disease conditions such as childhood diabetes 104 and obesity.105 However, Ezenwosu et al 26 in their study of academic performance of children with sickle cell disease aged 5-11 years also noted a similar trend of early decline in IQ in both children with SCA and their controls. They suggested that it was due to presence of silent cerebral infarcts that progress over the years and this has been implicated in cognitive impairment in children with SCA.26 However, they could not explain the paradox of similar trend of declining IQ with age among the controls. This trend of early decline in mean IQ in both subjects and controls however, may be related to the DAPT and study environment, which are common to this study and that of Ezenwosu et al.26 This unequal distribution of the study population across the different ages may also have influenced this finding. Decline in IQ in studies 104, 105 that used WISC were noted at later ages compared to what was found in this study and that of Ezenwosu et al 26 and in these studies 104, 105 the decline was said to be based on the properties of WISC test and the changes in the test over various ages.
In the WISC, at the early childhood level, there are many items such as single word vocabulary and visual matching tasks. By middle childhood, more abstract thinking and symbolic language are required, and wordings of questions are more complex. While the DAPT is said to demonstrate a high correlation with the WISC tests, 89 some other studies differ by rather demonstrating a low correlation between WISC and DAPT,106 no relationship between human figure drawings and IQ 107 suggesting that the DAPT should not be used as a substitute for other well- established intelligent tests like the WISC.106, 107 However, the WISC has not been validated for use in our environment and studies done before now on academic performance in our environment used the DAPT to assess IQ.23, 26
IQ had a linear relationship with academic performance in both subjects and controls. This is consistent with the observations by Javad 77 and Daramola.82 The study of children with SCA by lxxvi
Chodorkoff 80 as well as other studies74, 79, 81 also found a positive correlation between IQ and academic performance. IQ scores therefore may be an appropriate guide in the proper placement of school children with asthma at the beginning of their education.78
More children in the higher socio-economic class had good academic performance compared to children in the lower socio-economic class in both the subjects and controls. This is in alignment with the finding of previous studies.74, 75, 76 The larger proportion of children in higher socio- economic classes in this study may have influenced the finding of better academic performance among children in these classes compared to those in the lower socio-economic class. Parental motivation of these children from the upper socio-economic class via placement in good schools, extra lessons at school and at home may have contributed to the better academic performance seen among them.
However, Gutstadt and colleagues13 in their study reported that academic performance was not related to socio-economic class amongst children with asthma.73The difference between the findings in this study and that of Gutstadt could be due to differences in the environment where these studies were done as well as differences in the socio-economic status assessment tool used.
The reason suggested in a similar study, 26 for poor academic performance in children from low socio-economic background was that these children were more likely to miss school than their more affluent peers and also suffer from poor funding of education due to depleted family resources from patient care. Karadel and colleague74 attributed it to poor motivation, unsatisfactory home environment and neglect, poor housing and nutrition.
Although asthma control on its own does not influence academic performance, it is a predictor of academic performance as it has a significant positive effect on academic performance of the
lxxvii
subjects in the presence of other factors such as age, socio-economic class, school absence and
IQ. The larger proportion of subjects with good asthma control compared to those with poor asthma control in this study may have influenced this result. This was because selection of the subjects was from the asthma clinic where these children were being followed up regularly and therefore had more children with good asthma control. This finding on the effect of asthma control on academic performance in this study is in alignment with earlier studies. 6, 70, 71These studies 6, 70 suggested that poor asthma control caused poor academic performance through increase in school absence. However from this study it is unlikely as school absence was not found to significantly affect school performance in the subjects. A more recent study by Daphne
71 identified poor sleep quality due to poorly controlled asthma as the cause of this negative effect of asthma status on academic performance of these children. The psychological impact of poor asthma control on these children may also be contributory.77
Age had a significant negative effect on academic performance while school absence, IQ and socio-economic class had no significant effect on the academic performance of the subjects. This negative effect of increasing age on academic performance was also noted by Ibekwe et al 23 who suggested that increase stress and pressure from increasing school work load may be responsible. In addition, IQ was found in this study to be associated with improved academic performance thus the early decline in IQ with age noted in these children may also be contributory.
lxxviii
CONCLUSION
1. The overall academic performance of primary school children with asthma is similar to
that of non-asthmatic children in the same setting.
2. Although the mean number of days of school absence is higher in children with asthma,
there is no significant relationship between school absence and academic performance in
children with asthma.
3. Asthma control has a significant positive effect on academic performance.
lxxix
LIMITATIONS OF THE STUDY
This is a cross-sectional study and thus cannot establish a cause and effect relationship. Case- controlled longitudinal studies may be necessary.
lxxx
FURTHER RESEARCH NEED
There was an early decline in IQ with age noted amongst the Subjects and Controls. Male subjects performed significantly better overall and in Mathematics and Social studies compared to their Controls while female Subjects had a significantly higher mean IQ and performed poorer in English compared to their controls. Also while female controls performed significantly better overall and in the four key subjects compared to male controls; there was no significant difference in academic performance between male and female subjects. Further studies are needed to determine the reason for these findings.
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APPENDIX I
CONSENT FORM
Identification Number………………:
TITLE OF STUDY: A STUDY OF ASPECTS OF THE ACADEMIC PERFORMANCE AND ITS DETERMINANTS AMONG PRIMARY SCHOOL CHILDREN WITH ASTHMA ATTENDING THE UNIVERSITY OF NIGERIA TEACHING HOSPITAL, ENUGU STATE, NIGERIA.
Introduction: Dear respondent, you have been selected to participate in a study on: Aspects of Academic performance and its determinants among school children with asthma attending the University of Nigeria Teaching Hospital, Enugu state, Nigeria. The study is based on the assumption that the findings will help in counseling school children with asthma as regards their school performance and the provision of special educational resources/intervention, when necessary. The study is by Dr Nduagubam Obinna Chukwuebuka of the Dept. of Pediatrics, UNTH Enugu.
Voluntary nature of participation: Participation in this project is completely voluntary. Therefore, although you have been selected, you are free to participate in the program or to decide otherwise. If you decide to participate, you are free to withdraw from it at any stage of the program without any reprisal whatsoever.
Study procedure: You will be asked questions that will help in assessing the academic performance of children with asthma compared to non-asthmatic controls and identify factors that may influence the academic performance of these school aged children with asthma. You will be interviewed using questionnaire and other assessment tools. Your child will also be visited in his/her home and school for information on his/her academic record during the study period.
Confidentiality: Information obtained from you will be treated as confidential and will not be used against you in any form. In addition, data analysis and presentation from this study will be aggregate, and will not in any way reveal your identity.
Feedback: The Researcher will be at hand every time to answer any question(s) you may have concerning the project. Similarly, throughout the course of the study, the Researcher will be available to answer any question or deal with any problem that may arise. You can always reach the Principal Researcher on 07030488841 or personally at the Department of Pediatrics, University of Nigeria Teaching Hospital, Ituku/Ozalla Enugu.You can also reach the Chairman,
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Health Research Ethics Committee of UNTH through the Administrative Secretary/Desk Officer, Health Research Ethics Committee UNTH on 08034079903.
Thank you
Dr Nduagubam O.C
Principal investigator
I…………………………………………………………………………, mother,/father/caregiver of the child,
……………………………………………………, (Name of Child) have read and understood the above (or had someone read and explain the study to me). All the gray areas have been clarified. I fully understand the nature, risk and benefit of the study and hereby consent to take part in it.
Signature/thumb print of Caregiver………… Name of witness…………………………
Signature of witness……………………
Date: …………………………… Date: ……….………
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APPENDIX II
SOCIO-DEMOGRAPHIC DATA, PAST MEDICAL HISTORY RELEVANT CLINICAL INFORMATION
Name:……………………………………… ID No:……………. Hospital No…………………………… Address:…………………………………………………………………………………… Contact phone No………………………………………… Age:……….. Sex:………… School attended (in the last one year)……………………………………………………… Class …………… Term ………… Name of Class Teacher……………………………………………………………………… Father’s Educational Level…………………………… Mother’s Educational Level…………………………………………………………………. Father’s Occupation…………………………………… Mother’s Occupation………………………………………………………………………… Birth Order…………………………… No. of Siblings…………………………………
Medical History of participant: I Are u a diagnosed asthmatic patient Yes…No… If yes, When /How long…… II History of recurrent cough, Wheeze, chest tightness or difficulty Yes…No…... If yes, how often. More than 3 times a month ( ) 2 or 3 times a month ( ) once a month( ) occasionally( ) III History of: Jaundice Yes…… No……. Recurrent bone pains Yes…… No……. Blood Transfusion Yes… No……If yes, How many times…. Darkening of the lips and hands Yes…… No……. Easily tired Yes…… No……. Cough Yes…… No… If yes, for how long…… Weight loss/ poor weight gain Yes…… No……. Convulsions Yes…… No…….
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At how many months did he/she attain neck control? Yes…… No……. At how many months did he/she walk without support? Yes…… No……. Do you drink a lot of water/fluids? Yes….. No…….. Do you wake up more often now at night to pass urine? Yes…….No…… If yes how many times now? …How many times before…For how long?.. Do you eat a lot more than you used to? Yes…. No……. Do you have a history of diabetes in your family? Yes…… No……. Do you have any other illness Yes….. No……. If yes, specify………… Duration of illness……………………… Past emergency room visits Yes… No….. If yes, No of times in the last yr…… Past Hospital Admission(s) Yes… No… If Yes, no of times…………… Reason(s) for admission /Diagnoses……………………………………………………… Average Period of Hospital Stay per admission………….
Physical examination
General physical examination……………………………………………………………… ……………………………………………………………………………………………………… ……………………… Tempt………….. Pulse Rate……… Resp. rate……… Respiratory system……………………………………………………………………… Central nervous system …………………………………………………………………… ……………………………………………………………………………………………… Cardiovascular system exam………………………………………………………………… …………………………………………………………………………………………… Other relevant examination findings………………………………………………………… ………………………………………………………………………………
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APPENDIX III SOCIO-ECONOMIC INDEX SCORES (OYEDEJI’S) 97 ID No:………………..
Parental Occupation Father (A) Mother B)
Class
I. Senior public servants, Professionals, Managers, Large scale traders, Businessmen & Contractors.
II. Intermediate grade public servants, Senior School Teachers, Nurses and Technicians.
III. Junior School Teachers, Clerks, Auxiliary Nurses, Drivers and Mechanics.
IV. Petty traders, Laborers, Messengers and Similar Grades.
V. Unemployed, Full-time house wives, Students and Subsistence farmers.
Parental Educational Attainment
I. University graduates or equivalents.
II. School certificate holders (GCE or SSSC) who also had teaching or other professional training i.e. NCE.
III. School certificate or Grade II teachers’ certificate Holders or equivalents.
IV. Junior secondary school certificate, Modern three and primary six.
V. Those that could not just read or write or are illiterates.
Four scores are obtained from educational attainment and occupation of the 2 parents. The socio-economic class is obtained by the mean of aggregate of the 4 scores for the 2 parents. This is then rounded off to the nearest whole number to get the Socio-economic level of the subject.
Total Score [Sum of the total scores of father (A) and Mother (B)]
Socio-economic class index score, therefore is Total score = ……………………
4
APPENDIX IV xcvi
CHILDHOOD ASTHMA CONTROL TEST49 (FOR CHILDREN 4-11YRS)
ID No: ……………………
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APPENDIX V CONSENT FROM STATE MINISTRY OF EDUCATION
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APPENDIX VI DRAW A PERSON TEST (ZILER) 89 ID No…………………. A child is instructed to draw a complete person (no further instructions). In the Ziler test, there are 52 criteria for scoring. 1. Head present 2. Head < half and > 1/6 of the trunk. 3. Hair on the head. 4. Hair proportionately outlined 5. Eyes 6. Pupils 7. Eyebrow/eyelashes 8. Nose indicated (stroke or point) 9. Mouth indicated (stroke/s) 10. Nose plastic (two holes) 11. Mouth plastic (proper shape) 12. Lips clearly drawn 13. Chin clearly indicated or beard 14. Ears indicated 15. Ears plastic 16. Neck shown, head and trunk linked 17. Neck plastic with correct curves 18. Neck well joined to head/trunk 19. Trunk indicated 20. Trunk plastic and longer than broad 21. Shoulder clearly recognizable 22. Arms as a stroke
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23. Arms plastic 24. Arms well placed relative to face 25. Elbow shown at least on one arm 26. Hands shown correctly and plastic 27. Hands clearly drawn 28. Fingers indicated 29. Fingers plastic 30. Fingers with correct numbers 31. Thumb sticking out 32. Leg indicated 33. Legs plastic 34. Legs correctly placed 35. Knee with angle on at least one leg 36. Feet indicated 37. Feet plastic 38. Feet with heel or shoe with heel 39. Face, enface with most parts shown 40. Face, enface, plastic, all parts shown 41. Face profile, no mixture with enface 42. Face profile, plastic and complete 43. Trunk and arms in profile (only with 41and 42) 44. Legs and feet in profile (only with 41,42 and 43) 45. Head cover indicated 46. Head cover with detail 47. Body dress (not navel) indicated 48. Trousers/ skirts clearly drawn, not transported 49. Shirt/blouse clearly drawn, not transparent c
50. Collar clearly drawn 51. Shoe indicated 52. Shoe clear with details Four points count as 1 draw-a-person year. A child is not expected to score any point in this test until the age of four years. To compensate for this, 3 points are added to get the calculated draw- a-person age = [(points scored/4) + 3]. Draw a person quotient (DAPQ) = DAPA x 100% Chronologic age
Normal should be above 75%
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APPENDIX VII
TABLE OF DAPQ SCORES 89
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APPENDIX VIII
SCHOOL DATA/ REPORT
ID No:……………
Name of Child………………………………………………………………………………
Class in last Academic Session……………
No of students in the class…………………..
Academic Performance 1st Term 2nd Term 3rd Term
(I) Class Position ...... ……….. ………..
(ii) Overall Score ………. ………. ………..
(iii) % Score Mathematics ………. ……….. ………..
(iv) % Score English ………. ……….. ………..
(v) % Score Social Studies ………. ……….. ………..
(vi) % Score Science ………. ……….. ………..
Total no. of days absent from school ………. ..……… ………..
Total No of days absent from school for the year …………
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APPENDIX IX ETHICAL CLEARANCE
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APPENDIX X ETHICAL CLEARANCE
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