Magnitude of Attention Deficit Hyper Kinetic Disorder among School Children of Mysore City

Abstract

Background: Attention Deficit Hyperkinetic Disorder (ADHD) is a highly prevalent disorder of Childhood and adolescence. There are only a few studies reporting the prevalence of this condition. Methods: This cross-sectional study was conducted in three primary school; children aged 6-10 years of Mysore city, using Conner's 3 Parent short form. A total of thousand hundred and forty five children participated in the study. Results: The overall prevalence of ADHD was 14.4%. The prevalence of ADHD Inattentive, Hyperactive and Combined type was 4.1, 3.4 and 6.9% respectively. The male female ratio was 1.8:1. Paternal alcohol consumption (OR 2.36) and lack of breast feeding (OR 2.43) were found to be predictors of ADHD. Aggression/Defiance and Learning Difficulties were observed in 63 and 58.2% respectively. Conclusion: This study noticed a very high prevalence of ADHD. Increasing awareness among parents and teachers about the disorder can lead to early identification and management.

Full text

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*Corresponding author: E-mail: dr.renuka.m@gmail.com;
International Neuropsychiatric Disease Journal
6(1): 1-7, 2016; Article no.INDJ.21954
ISSN: 2321-7235, NLM ID: 101632319
SCIENCEDOMAIN international
www.sciencedomain.org
Magnitude of Attention Deficit Hyper Kinetic
Disorder among School Children of Mysore City
Renuka Manjunath
1*
, M. Kishor
2
, Praveen Kulkarni
1
, B. M. Shrinivasa
1
and Saigopal Sathyamurthy
1
1
Department of Community Medicine, JSS Medical College, Mysore, India.
2
Department of Psychiatry, JSS Medical College, Mysore, India.
Authors’ contributions
This work was carried out in collaboration between all authors. Authors RM and MK designed the
study and wrote the protocol. Author MK translated the study tool. Authors PK and BMS supervised
the statistical analysis and reviewed the manuscript. Author SS preformed the statistical analysis,
managed the literature search and wrote the first draft of the manuscript with supervision from authors
PK and BMS. All authors read and approved the final manuscript.
Article Information
DOI: 10.9734/INDJ/2016/21954
Editor(s):
(1) Andrea Martinuzzi, Department of Neurology and Neurorehabilitation, University of Padova, Italy.
Reviewers:
(1)
Syed Ali Raza Kazmi, Institute of Biomedical and Genetic Engineering, Islamabad, Pakistan.
(2)
Saleh M.H. Mohamed, University of Groningen, Netherlands.
Complete Peer review History:
http://sciencedomain.org/review-history/12394
Received 10
th
September 2015
Accepted 7
th
November 2015
Published 21
st
November 2015
ABSTRACT
Background:
Attention Deficit Hyperkinetic Disorder (ADHD) is a highly prevalent disorder of
Childhood and adolescence. There are only a few studies reporting the prevalence of this condition.
Methods: This cross-sectional study was conducted in three primary school; children aged 6-10
years of Mysore city, using Conner’s 3 Parent short form. A total of thousand hundred and forty five
children participated in the study.
Results: The overall prevalence of ADHD was 14.4%. The prevalence of ADHD Inattentive,
Hyperactive and Combined type was 4.1, 3.4 and 6.9% respectively. The male female ratio was
1.8:1. Paternal alcohol consumption (OR 2.36) and lack of breast feeding (OR 2.43) were found to
be predictors of ADHD. Aggression/Defiance and Learning Difficulties were observed in 63 and
58.2% respectively.
Conclusion: This study noticed a very high prevalence of ADHD. Increasing awareness among
parents and teachers about the disorder can lead to early identification and management.
Original Research Article

Manjunath et al.; INDJ, 6(1): 1-7, 2016; Article no.INDJ.21954
2
Keywords: Attention deficit hyperkinetic disorder; rating scales; school children.
ABBREVIATIONS
Attention Deficit Hyperactivity Disorder=ADHD; Conner’s 3 Parent short form= C3P(S); Inattention=
(IN); Hyperactivity/impulsivity= HY; Learning Problems= LP; Executive Functioning= EF;
Aggression/Defiance= A/D; Peer Relations= PR; Attention Deficit Hyperactivity Disorder- Combined
type= ADHD-C; Attention Deficit Hyperactivity Disorder- predominantly Inattentive type= ADHD-I;
Attention Deficit Hyperactivity Disorder- predominantly Hyperactive/Impulsive type (ADHD-H).
1. INTRODUCTION
Children and adolescents constitute around 40%
of Indian population. Attention Deficit
Hyperactivity Disorder (ADHD) is one of the most
common neuropsychiatric conditions of childhood
and adolescence. In India, the prevalence of
ADHD in Child Guidance Clinics ranges between
8%-20% [1],[2],[3],[4]. This disorder persists into
adolescents and adulthood causing secondary
psychosocial problems such as early onset
alcohol dependence, non-alcoholic substance
abuse disorder and anti-social personality
disorder [5],[6],[7],[8].
Children’s hyperactivity can also be very stressful
for the caregivers. Both teachers and parents
can find it difficult to handle a hyperactive child,
and their tolerance and ability to cope may
determine whether it is presented as a problem.
The disorder also increases parental stress
[9],[10].
Disruptive behavioral disorders and learning
disorders are the frequently associated co-
morbid condition [11]. Children suffering ADHD
are often labeled as naughty/ under-achiever and
are not referred. With a steady rise in the juvenile
delinquents and increase in crime rates, there is
a necessity to emphasis on this particular age
group.
This is cross-sectional study was undertaken to
know the magnitude of ADHD and the various
socio-demographic characteristics associated
with it. Sharing the study result will also help in
sensitizing the parents and teachers about the
disorder.
2. MATERIALS AND METHODS
This cross-sectional study was conducted in
Mysore city during January 2014- April 2014.
Mysore has 557 schools out of which 390
schools were offering primary school education.
The sample size calculation was made on the
basis of a study conducted in Coimbatore, India
[12] to determine the prevalence of ADHD
among primary school children aged 6-11 years,
which was found to be 11.33%; considering an
absolute precision of 2% with 95% confidence
interval, the sample size required for our study
was found to be 968.
Two stage sampling was adopted to identify the
study participants. The schools offering primary
school education in Mysore city was the unit of
sampling in first stage. Utilizing the school list as
a sampling frame, schools were selected by
simple random sampling which was done using
random number table. In the second stage all
eligible children in the schools were selected till
the saturation was met. In this process, three
were included for the study.
The tool used was Conner’s 3 Parent short form
C3P(S) [11]. The Conner’s 3 is a focused
assessment tool for ADHD and associated
issues in children ages 6 to 18 years. Its content
scales include inattention (IN),
hyperactivity/impulsivity (HY), learning problems
(LP), executive functioning (EF),
aggression/Defiance (A/D) and peer relations
(PR). The Cronbach’s alpha for C3P(S) ranges
from 0.85 to 0.92 [13]. The tool was validated
and had the questions both in English and
Kannada. Socio-demographic information was
collected using a semi-structured questionnaire.
After acquiring a formal permission from the
Principal of each selected schools, school
children were briefed about the purpose of the
study in their respective class and the study tool
along with the parent consent form was
distributed. For children who were not living their
parents, their guardians were invited to rate the
child’s behavior. Completed forms were collected
over a period of three days. Children of parents
who give consent for participation were included
in the study. Those children identified with
disorder were offered consultation with
psychiatrist at a tertiary care hospital.
The raw scores are added up for each content
scale and converted to T scores (transformed
scores). This transformation was based on the
mean and standard deviation of raw scores of a
normative sample of American children of the

Manjunath et al.; INDJ, 6(1): 1-7, 2016; Article no.INDJ.21954
3
same age and sex. Transformation was done
using Conner’s 3
rd
edition manual. The
transformation formula is 50+10[(raw score of a
domain – mean of that domain in normative
sample)/ standard deviation of that domain in
normative sample].
Transformed score of >65 in both inattentive &
hyperactive/impulsive domain with elevated
scores (>65) in any of the other domain was
defined as Attention deficit hyperactivity disorder-
combined type (ADHD-C). Elevated scores in
only inattentive and any of the other domain was
defined as Attention deficit hyperactivity disorder-
predominantly inattentive type (ADHD-I) &
elevated scores in only hyperactive/impulsive
and any of the other domain was defined as
Attention deficit hyperactivity disorder-
predominantly hyperactive/impulsive type
(ADHD-H).
3. RESULTS
The analysis included the data of 1145 primary
school children from three schools of Mysore
city. For analysis involving socio-economic status
analysis, 992 subjects were included due to
missing values.
3.1 Socio-demographic Characteristics
The proportion of 6 to 10 year old was 19.8, 20.3,
20.4, 19.5 & 19.9 respectively. There were 578
(50.5%) boys & 567 (49.5%) girls. Majority of the
study subjects 1120 (97.6%) lived with their
parents.
3.2 Prevalence
Out of 1145 children studied, 165 (14.4%) were
found to have ADHD based on C3P(S). The
prevalence of ADHD-C was 6.9% (95% CI 5.5,
8.5), ADHD-I 4.1% (95% CI 3.1. 5.3) and ADHD-
H 3.4% (95% CI 2.4, 4.5). The prevalence was
more in boys18.5% compared to girls10.2%. The
male to female sex ratio was 1.8:1. The most
common associated problem with ADHD was
Aggression/Defiance (63%) followed by learning
problem (58.2%).
3.3 Factors Associated with ADHD
The factors which were associated with ADHD
are shown in Table 2. The Mean birth weight
children with ADHD was 3.13±1.86 as compared
to children without ADHD 3.01±0.55 (p value
.075) All the variables which were significant in
bivariate analysis (Chi-square & unpaired ‘t’ test)
were included in regression analysis. Multinomial
Logistic regression was used with ADHD status
as dependent variable. The reference was
children who were classified as normal by the
scale. The risk of ADHD-I, ADHD-C and ADHD-H
were estimated. Factors which were tested for
association were sex, father’s and mother’s
education, type of family, Paternal alcohol
consumption, breast feeding, family and sibling
H/O similar behavior.
4. DISCUSSION
The prevalence of ADHD in the present study
was found to be 14.4% (95% CI 12.33, 16.47)
Table 1. Socio-demographic characteristics of study participants (N=1145)
Socio-demographic characteristics Number Percentage
Type of family
Nuclear family 744 65.0
Joint family 401 35.0
Father’s education
Degree/diploma 772 67.4
High school/PUC 166 14.5
Others 207 18.1
Mother’s education
Degree/diploma 592 51.7
High school/PUC 260 22.7
Others 293 25.6
Father’s occupation
Professional/semiprofessional 217 19.0
Business/agriculturist/clerical 718 62.7
Others 210 18.3
Mother’s working status
Working 239 20.9
Not working 906 79.1

Manjunath et al.; INDJ, 6(1): 1-7, 2016; Article no.INDJ.21954
4
with majority being ADHD-C (6.9%). The male to
female sex ratio was 1.8:1. Table 4 compares the
results of this study with those present in
literature with samples greater than 100 & using
standardized diagnostic instruments.
The result of this study was similar to most of the
other studies except the studies conducted by
Prem Lata Chawla [14], Manilal Gada [15] &
Prahbhjot Malhi [3]. The reason for the difference
in the first two studies may be due to the
stringent diagnostic criteria used. The second
study also did not report the prevalence of ADD.
The 3
rd
study which was a hospital based study
recorded a lower prevalence than our study. The
reason may be due to different age group studied
as many studies noticed higher prevalence in
older age group [2],[12],[17].
Table 2. Univariate analysis of factors associated with ADHD [Mean±SD or n (%)] (N=1145)
Variable ADHD-C ADHD-I ADHD-H ADHD-any type p value
Gender
Male 54(9.3) 26(4.5) 27(4.7) 107(18.5) .000
Female 25(4.4) 21(3.7) 12(2.1) 58(10.2)
Family type
Nuclear 60(8.1)
*
29(3.9) 27(3.6) 116(15.6) .114
Joint 19(4.7) 18(4.5) 12(3.0) 49(12.2)
Birth order
1sr born 45(6.5) 23(3.3) 25(3.60 93(13.4)
2
nd
born 30(7.3) 19(4.6) 13(3.1) 62(15.0) .080
3
rd
born 3(9.1) 5(15.2) 1(3.0) 9(27.3)
4
th
born 1(33.3) - - 1(33.3)
Socio-economic status
Class I 28(5.7) 12(2.5) 17(3.5) 57(11.7)
Class II 18(7.4) 8(3.3) 7(2.9) 33(13.6)
Class III 21(11.7) 5(2.8) 8(4.4) 34(18.9) .206
Class IV 1(1.5) 4(6.1) 5(7.6) 10(15.2)
Class V 1(6.2) 2(12.5) - 3(18.7)
H/O Breast feeding
Yes 66(6.2) 40(3.8) 35(33.3) 141(13.3) .000
No 13(15.7) 7(8.40 4(4.8) 24(28.9)
Mother working Status
Working 63(7.0) 33(3.6) 32(3.5) 128(14.1) .471
Homemakers 16(6.7) 14(5.9) 7(2.9) 37(15.5)
Paternal alcohol consumption
Yes 14(13.5)
*
3(2.9) 2(1.9) 19(18.3) .061
No 65(6.2) 44(4.2) 37(3.6) 146(14.0)
Father’s occupation
Professional/Semi-professional 6(2.8) 1(0.4) 6(2.8) 13(6.0)
Business/Agriculture/Clerical 52(7.2) 24(11.4) 12(5.7) 95(13.2) .000
Others 21(10.0) 24(11.4) 12(5.7) 57(27.1)
Family H/O similar behavior
No 75(6.7) 40(3.6) 38(3.4) 153(13.7) .000
Yes 4(15.4) 7(26.9) 1(3.8) 12(46.2)
*
Significant difference observed when considered only for ADHD-C
Table 3. Predictors of ADHD
Diagnosis Variable Adjusted odds ratio 95% CI p value
ADHD-C
Sex (male) 2.12 1.28, 3.54 0.004
Not breastfed 2.43 1.2, 4.92 0.013
Paternal alcohol consumption 2.36 1.22, 4.55 0.01
Father being
businessmen/clerical/agriculturist 3.18 1.29, 7.83 0.12
Other occupations 3.39 1.17, 9.77 0.024
ADHD-I Other occupations 14.18 1.17, 117.3 0.014
Family H/O 7.56 1.96, 29.08 0.003
ADHD-H Sex (male) 2.32 1.14, 4.7 0.02
Nagelkerke pseudo R square= 0.16(16%); *- Father being professional/semi-professional was
the referent group in occupation

Manjunath et al.; INDJ, 6(1): 1-7, 2016; Article no.INDJ.21954
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Table 4. Indian studies in literature regarding the prevalence of ADHD
Author Year Setting Study population
age (yr) Sample Instrument Diagnostic criteria Prevalence (%)
95% CI M:F
ratio
Prem Lata Chawla
[14] 1982 CB 6-12 2160 Modified behavioral checklist ICD 4.67
3.7, 5.7 4.7:1
Manilal Gada [15] 1987 CB 5-10 321 Modified Conner’s Teacher scale DSM-III
*
(ADDH) 8.10
5.1, 11.1 7.6:1
M.S. Bhatia [4] 1999 HB 3-12 362 Clinical interview DSM-IV 17.7
13.7, 21.7 3:1
Prahbhjot Malhi [3] 2000 HB 3-12 245 Multimodal assessment DSM-IV 8.1
4.6, 11.5 5:1
Maya
Mukhopadhyay [2] 2003 HB 5-12 238 Clinical interview DSM-IV 15.5
10.8, 20.2 6.4:1
Venkatesh C [1] 2004 HB - 251 Multimodal assessment DSM-IV 20.3
15.2, 25.3 6.3:1
BS Suvarna [16] 2009 CB 4-6 1250 Conner’s Global Index DSM-IV TR 12.2
10.6, 14.0 3.3:1
Venkata JA [12] 2013 CB 6-11 635 Conner’s Abbreviated Rating Scale
(CARS) DSM-IV TR 11.33
8.8, 13.8 1.9:1
This study 2104 CB 6-10 1145 Conner’s 3 Parent short form DSM-IV TR 14.4
12.3,16. 1.8:1
CB- Community Based; HB- Hospital Based; ADDH- Attention Deficit Disorder with Hyperactivity
DSM-III classify; ed the disorder as ADDH, ADD (Attention Deficit Disorder without Hyperactivity) & Residual type (ADD-RT)

Manjunath et al.; INDJ, 6(1): 1-7, 2016; Article no.INDJ.21954
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The prevalence was higher in males with male to
female ratio ranging between 1.8:1 to 7.6:1.
Higher male to female ratio was noticed in
studies which measured the severe form (ADHD-
C) & in hospital based studies. This may be due
to the higher referral rate for boys & higher level
of hyperactivity associated with boys. Present
study found sex was an independent predictor for
ADHD-C & ADHD-H.
Breastfeeding (not breast fed) was also found to
be predictor for ADHD-C in this study, supported
by other studies like, a case control study done
by Aviva Mimouni-Bloch [18] in Israel on 6-12 yr
old, using 2 control group of non-ADHD sibling &
non-ADHD hospital control found that lack of
breastfeeding at three months as a risk
factor.(odds 95% CI 1.46-6.50). Similarly, a
cross-sectional study conducted by Hamed JHA
[19] in Saudi Arabia found that children who are
not breastfed are at a higher risk of ADHD-I.
Contrary to the theory that ADHD has a strong
genetic background, family history of similar
behavior was able to predict only ADHD-I in our
study. This can be attributed to reporting bias, as
behavioral/mental disorders in the family are
perceived as weakness. However Children with
Inattentiveness, because of the commonly
associated learning problem, are often labeled as
underachiever and this is not considered by the
parents as a behavioral disorder. Low socio-
economic status showed no association with
ADHD and/ or Hyperkinetic disorder in contrast
to several studies [4],[12],[14]. This may be due
to very less number of study participants in class
V socio-economic status according to BG Prasad
scale in our study (1.6%). However, father’s
occupation was significantly associated with
ADHD-C & ADHD-I in our study.
5. CONCLUSION
A high prevalence of 14.4% of ADHD among
children warrants for an active detection and
intervention since, it can significantly affect a
child scholastic performance, family and peer
relation. It is clear that the prevalence of ADHD
varies widely within and outside a country. The
reasons for these differences are different
diagnostic criteria, different diagnostic approach,
different tools even if the approach is same,
different study setting, cultural difference in
tolerability of hyperactive behavior, rater’s
psyche. Although the condition is more common
in boys in hospital settings, this difference is less
at community level. With many independent
predictors which are preventable such as breast
feeding and paternal alcohol consumption,
addressing these issues would prevent the
occurrence and influence the outcomes.
6. RECOMMENDATIONS
Focus on preventable causes such as by
creating awareness and promoting breast
feeding, awareness on the ill effects of alcohol
consumption and its influence on ADHD would
bring about substantial benefits in reducing the
burden. A standardized tool for parent and
teachers to detect ADHD would decrease the
arduous task of the present scenario. At
community level, a stepped care model proposed
by NICE can be applied [20]. This consists of
multiple assessments at tier 1 by teachers,
parent & other healthcare professional, which in
turn would sensitize them about this condition for
the early diagnosis & timely referral. Future
follow up studies of this cohort planned would
reveal about the progress of the disorder.
7. STRENGTHS AND LIMITATIONS
The strength of the study include use of
standardized tool, community based study, large
sample size and generalizibility of result to the
Mysore population. The findings of our study
need to be considered alongside the following
limitations. Reporting bias are a limiting factor in
parents who want to mask the true status of their
child. Another limitation was child’s behaviour
was assessed by only one individual rating, the
simultaneous use of teacher’s rating scale could
have yielded more information. This being a
cross-sectional study cannot confirm causality
between factors.
INSTITUTIONAL ETHICS CLEARANCE
AND CONSENT
The study was approved by the institutional
Ethics Committee and formal written permission
was obtained from the Heads of each school.
COMPETING INTERESTS
Authors have declared that no competing
interests exist.
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Peer-review history:
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