|Year : 2016 | Volume
| Issue : 2 | Page : 131-137
Prevalence of mental retardation in urban and rural populations of the goiter zone in Northwest India
Shailja Sharma1, Sunil Kumar Raina2, Ashok Kumar Bhardwaj3, Sanjeev Chaudhary4, Vipasha Kashyap5, Vishav Chander2
1 Resident, Department of Community Medicine, Dr. Rajendra Prasad Government Medical College, Kangra, Himachal Pradesh, India
2 Associate Professor, Department of Community Medicine, Dr. Rajendra Prasad Government Medical College, Kangra, Himachal Pradesh, India
3 Professor, Department of Community Medicine, Dr. Rajendra Prasad Government Medical College, Kangra, Himachal Pradesh, India
4 Professor, Department of Paediatrics, Dr. Rajendra Prasad Government Medical College, Kangra, Himachal Pradesh, India
5 Clinical Psychologist, Department of Community Medicine, Dr. Rajendra Prasad Government Medical College, Kangra, Himachal Pradesh, India
|Date of Web Publication||23-Jun-2016|
Sunil Kumar Raina
Department of Community Medicine, Dr. Rajendra Prasad Government Medical College (RPGMC), Tanda, Kangra, Himachal Pradesh
Source of Support: None, Conflict of Interest: None
| Abstract|| |
Background: The existence of an endemic goiter belt along the southern slopes of the Himalayas has been known for a long time. Prevalence of neonatal hypothyroidism is high and there has been little work on the prevalence of mental retardation in this part of India. Objective: The study was conducted with the aim to know the prevalence of mental retardation in the urban and rural populations of Himachal Pradesh, India and to generate a hypothesis on the differential distribution (geographical) of mental retardation. Methods: This cross-sectional study was conducted in the rural and urban areas of the district of Kangra, Himachal Pradesh, India among children of 1-10 years of age. In the first phase, the children in the age group of 1-10 years were screened for mental retardation using the Ten Questions Screen, whereas in the second phase the suspects were evaluated clinically. Results: The prevalence of mental retardation was found to be 1.71% in the study population with higher prevalence (3.3%) in the 73-120 months age group. The prevalence was higher among the males in all study populations [rural: 1.9%, urban (nonslum): 1.6%, and urban slum: 7.14%). The prevalence was similar among the urban (nonslum) (1.75%) and rural (1.11%) populations, whereas it was higher (4%) in the urban slum population. A prevalence of 2% was seen in families from the lower middle class and 1.8% among families from the lower class in the rural population, whereas a prevalence of 2% was seen among lower middle class families of urban (nonslum) areas. Conclusion: The prevalence of mental retardation was higher in our study than in other parts of the country. The study concludes with the hypothesis that the prevalence of mental retardation is differentially distributed geographically with socioeconomic factors being important predictors.
Keywords: Goiter zone, India, mental retardation, prevalence
|How to cite this article:|
Sharma S, Raina SK, Bhardwaj AK, Chaudhary S, Kashyap V, Chander V. Prevalence of mental retardation in urban and rural populations of the goiter zone in Northwest India. Indian J Public Health 2016;60:131-7
|How to cite this URL:|
Sharma S, Raina SK, Bhardwaj AK, Chaudhary S, Kashyap V, Chander V. Prevalence of mental retardation in urban and rural populations of the goiter zone in Northwest India. Indian J Public Health [serial online] 2016 [cited 2020 Jan 25];60:131-7. Available from: http://www.ijph.in/text.asp?2016/60/2/131/184545
| Introduction|| |
The World Health Organization (WHO) estimates that globally over 450 million people suffer from mental disorders. Currently, mental and behavioral disorders account for 12% of the global burden of disease. This is likely to increase to 15% by 2020. The major proportions of mental disorders come from low- and middle-income countries. The problem is further complicated by a lack of adequate trained manpower and a low priority of mental health in health policy. 
The etiologies of mental retardation are multiple, and prevalence can be influenced by social, economic, cultural, racial, ethnic, and other environmental factors including the demographics of age and gender. Various studies have consistently found the prevalence of mental retardation to be associated with a low socioeconomic status. 
On the basis of the nature of the factors, causes may be classified as environmental and genetic. Environmental causes can affect a child via pre- and postnatal exposures. There are numerous environmental factors that often contribute to mental retardation. Toxins such as lead and mercury affect mental health. Iodine deficiency affecting about 2 billion people all over the world is the leading preventable cause of mental disability in areas of the developing world where iodine deficiency is endemic. Lack of adequate availability of iodine from the mother restricts the growth of the brain of the fetus and leads to a condition called neonatal hypothyroidism. In India, about 150 million people are at risk of iodine deficiency disorder, 54 million have goiter, and 2.2 million suffer from cretinism. 
Endemic goiter exists in an extensive belt along the southern slopes of the Himalayas and this has been known for a considerable time. The goiter belt covers 2,400 km and is one of the most intense areas of endemic disease. Faced with the goiter problem of a great magnitude, the Government of India in collaboration with the Government of Punjab and the Indian Council of Medical Research (ICMR) decided in 1954 to undertake a systematic field experiment to demonstrate the effectiveness of iodine when added in small physiological doses as a supplement to the common salt habitually consumed by the people in endemic areas in the prevention of goiter (the Kangra valley study). 
The present study has been conducted with the aim to know the prevalence of mental retardation in the urban and rural populations of Himachal Pradesh and to generate a hypothesis on the differential distribution (geographical) of mental retardation in the goiter belt of the sub-Himalayan region.
| Materials and Methods|| |
This study was conducted in the urban, rural, and slum populations of the district of Kangra in Himachal Pradesh, India. For the purpose of the study, nine wards of Kangra town with a population of 9,528, along with its slum population were considered for the urban (nonslum and slum) population while Shahpur block with a population of 136,000 and Nagrota Bagwan block with a population of 115,767 were considered for the rural population. The study was conducted for a period of 1 year from January 1, 2013 to December 31, 2013. The study population included children in the age group of 1-10 years of age from the selected areas. The study was approved by the institution ethics committee.
The sample size calculation was based on WHO guidelines for population-based assessment of disabilities. In the WHO publication "Development of indicators for monitoring progress towards health for all by the year 2000," a sample size of 1,000 is recommended for covering all disabilities. But if the survey is aimed at assessing specific disorders, such as mental retardation, a sample size of 5,000 is suggested.  To achieve the most accurate estimates, it is advisable to conduct a house-to-house survey in three areas: one urban slum (including urban slum areas around the capital or any other major city) and two rural areas, one that is relatively economically prosperous and one that is poor. 
Keeping this in view, a sample of 5,000 children was planned from the urban area including its urban slum area and rural areas (Shahpur and Nagrota Bagwan areas) as mentioned earlier. However, to round off the sample distribution in these areas, a total of 5,300 children who were 1-10 years of age (500 from urban and 4,800 from two rural areas) were included in the study. The study population of 5,300 was divided in a proportion of 90% and 10% between the rural and urban areas, respectively, in accordance with the demographic distribution prevalent in Himachal Pradesh.  The study design comprised a stratified two-stage sampling. The design was similar in rural and urban areas.
Kangra town is distributed around nine urban wards and has one slum area attached to it. The wards and the slum area formed the primary sampling unit, and the children the secondary unit. Fifty children from each of the nine wards of Kangra town (described as urban nonslum and hereafter referred to as urban area) and the urban slum area (hereafter referred to as slum area) were included in the study, giving us the required sample size of 500 children.
Samples were derived from two blocks: Nagrota Bagwan and Shahpur. The villages formed the primary sampling unit, and the children the secondary unit. The 30-cluster technique primarily used to estimate immunization coverage was used as a strategy to pick up the primary sampling units. Before the sampling began, the population was divided into a complete set of nonoverlapping subpopulations (clusters) with a defined geography (villages). After this, 30 of these clusters were sampled with probability proportionate to the size (PPS) of the population in the cluster. A cluster of 30 villages was taken from each block. About 80 children taken from each cluster were included in the study to complete a sample requirement of 2,400 children from each block. In case of insufficient number of children in a single cluster, children in the adjoining village were included.
Parental permission was sought before including children up to 7 years of age in the study after ensuring the following:
- The process conducted in a manner and location that ensured the participant's privacy.
- Giving adequate information about the study in a language understandable to the participant.
- Providing adequate opportunity for the participant to consider all options.
- Responding to the participant's questions.
- Ensuring that the participant understood the information provided.
- Obtaining the participant's voluntary agreement to participate.
- Continuing to provide information as required by the participant or the research.
In children above 7 years of age, assent from children in addition to parental permission after fulfilling the above criteria was obtained.
Thus, from each village and urban ward children less than 10 years of age were selected. Once the children were identified, an evaluation was performed. The evaluation was conducted in two phases:
- Screening phase, and
- Clinical evaluation.
Phase I (screening phase)
Information about the child was preferably sought from the parents of the child. If the parents were not available, the same information was collected from any adult respondent present in the house at that time. After the beneficiaries were identified, a screening questionnaire was administered to identify children suspected of mental retardation. The screening questionnaire had been prepared in accordance with the Ten Questions Screen for the disability previously used in similar studies. 
The questionnaire was translated into the local language and administered during a personal interview after establishing the validity of the translated version by a reiterative technique with the parent or guardian. The details are provided elsewhere. 
The Ten Questions Screen is a brief questionnaire designed to screen serious cognitive, motor, seizure, vision, and hearing disabilities among young children in surveys of a culturally diverse population. ,,,,, Five of the questions focus specifically on cognitive development, two questions relate to movement disability, and one question each focuses on seizures, vision, and hearing, respectively.
Using a global rather than a disability-specific interpretation of the ten questions,  a child was considered positive for any disability if a response to any one question indicated potential disability. Using the global definition, the Ten Questions Screen has been shown to have good reliability  and validity (sensitivity 85%) for detecting severe neurodevelopmental disabilities.  In addition to the Ten Questions Screen, a structured pro forma was administered to collect demographic information about each child and his/her household. In addition, inquiries on details of the socioeconomic status of the child were made using the Uday Pareek scale in the rural areas and Kuppuswamy scale in the urban areas.
Phase II (clinical evaluation)
All children who screened positive were referred for clinical evaluations. Clinical evaluation was performed (without the knowledge of the screening result) by a pediatrician. The diagnosis of mental retardation was made after psychological assessment based on nonverbal scales from the 1985 revision of the Stanford-Binet intelligence test.  The assessment of mental retardation was also based on the child's developmental history and a structured observation of the child's functioning in language, response to instructions, and his or her ability in motor skills and behavior. The classification of a child as mentally retarded implied "significantly sub average intellectual functioning existing concurrently with related limitations in two or more of the following applicable adaptive skill areas with such limitations manifested 'before age 18':  communication, self-care, home living, social skills, community use, self-direction, health and safety, functional academics, leisure, and work.
| Results|| |
Ninety-one children out of a total of 5,300 turned out to be suffering from mental retardation, giving an overall prevalence of 1.71%. Mental retardation was 6.82 times more among children 73-120 months of age as compared to 12-36 months [odds ratio (OR) = 6.82; confidence interval (CI) = 2.96-15.69) and the association was highly significant (P = 0.001) [Table 1]. Mental retardation was more among males in the rural, urban, and the slum populations as compared to the female population [Table 2]. The difference however, was not found to be statistically significant [Table 3]. Amongst the 500 children examined in Kangra town, the highest prevalence of 1.4% was seen in the age group of 37-72 months with an OR of 1.5 (CI = 0.136-17.05) although the association was not statistically significant (P = 0.73).
|Table 1: Agewise prevalence of mental retardation in the study population|
Click here to view
|Table 2: Genderwise prevalence of mental retardation in the study population|
Click here to view
|Table 3: Association between the prevalence of mental retardation and gender|
Click here to view
A total of 50 children were screened in the adjoining slum area of Kangra town. Out of them, only two were mentally retarded. Both were males. One was 12-36 months of age, whereas the other was in the age group of 37-72 months. All the families screened belonged to the upper lower class.
[Table 4] provided details on the prevalence of mental retardation among participants belonging to different socioeconomic classes. The difference was statistically significant in the rural area only.
| Discussion|| |
Ninety-one children out of a total of 5,300 turned out to be suffering from mental retardation, giving an overall prevalence of 1.71%. However, there was a clear-cut difference in the prevalence of mental retardation among different geographically located population groups. Globally, the prevalence of mental retardation has a variance of 1-3%.  The prevalence rate in the Metropolitan Atlanta Developmental Disability Study conducted from 1985 to 1987 was reported to be 12 per 1,000 in children of 10 years of age. In a critical review of the literature published in 1997, 43 studies conducted across the world and published between 1981 and 1995 were analyzed, reporting a prevalence of 3.8 per 1,000 (for severe mental retardation).  The present study did not specify the severity of the disease while diagnosing mental retardation. However, the Ten Questions Screen that was used in the study generally detects cases with severe mental retardation.
In India, the National Sample Survey Organisation (NSSO) showed a prevalence of 0.95%.  Raina et al. in a study in Jammu and Kashmir reported a prevalence of 0.70%  and Ganguly et al. in their review of studies on mental disorders in India, reported a prevalence of 0.53%. 
Mental retardation in the present study was higher (3.3%) among children in the age group of 73-120 months as compared to the younger age groups. Similar results were seen in several other population-based studies conducted on children who were 5-19 years of age where a higher prevalence of mental retardation was seen in the older age group.  The reason for such a trend could possibly be attributed to the difficulty in diagnosis at an early age. When these mentally retarded children attend school, they are likely to be discovered by their teachers.  Such children were also noticed when they approached the health facility for specialty services such as visiting the doctor or making a disability certificate for availing concessions.
The prevalence of mental retardation in the present study was higher among males in all the three study populations, i.e., the rural (1.9%), urban (1.6%), and slum (7.14%) populations. Increased prevalence among the male children in the present study was in accordance with various studies conducted globally. In their study in Bangladesh, Islam et al. reported a higher prevalence among male children  just as Durkin et al. reported similar findings in Karachi, Pakistan.  In a study on the etiological spectrum of mental retardation and developmental delays, Aggarwal et al. have stated that increase in the prevalence among male children could probably be due to underreporting of mental retardation in female children.  Carolyn et al. in an analysis of the data from the Metropolitan Atlanta Developmental Disabilities Study have reported a higher prevalence of mental retardation among boys. However, they too attributed this male gender predominance among those affected to sex-based difference in treatment and referral pattern, and to the increased presence of sex-linked disorders such as the fragile X syndrome in boys. 
Durkin et al. in their study in Karachi, Pakistan have reported a higher prevalence of mental retardation in the rural areas as compared to urban areas.  A significant association was observed between mental retardation and the socioeconomic status of the family of the study population. The highest prevalence was seen among children from the lower middle class (2%) and lower class (1.8%) in the rural areas and lower middle class in the urban areas (2%). Children from economically disadvantaged families tend to score lower on intelligence quotient (IQ) tests than children from affluent families. Various factors in the child's environment due to the socioeconomic condition of the family contribute to the intellectual development of the child. 
Carolyn et al. in their work on sociodemographic risk factors for mental retardation have stated that isolated mental retardation rarely occurs in children from a higher socioeconomic status unless the child has sustained some biological damage, and that isolated mental retardation is associated with the economic condition of the family.  In their work on prevalence of mental retardation among children in Metropolitan Atlanta Murphy et al. have mentioned the effects of socioeconomic factors on the higher prevalence of mental retardation among Black children.  Some studies mentioned the sensory deprivation of children from poor backgrounds due to lack of toys to play with and fewer objects of any kind to stimulate their imagination. Lead poisoning from eating paint chips is a condition exclusively associated with poverty. The higher rate of birth defects and other conditions associated with brain damage are present in the poorer sections. 
Mental retardation has a vast spectrum of etiologies ranging from genetic, environmental, and metabolic. Iodine deficiency forms one of the major preventable causes of mental retardation. In a study conducted in the district of Kangra, the prevalence of neonatal hypothyroidism was found to be 4.4%,  which is much higher than the national prevalence which ranges from 1.6 per 1,000 to 1 in 3,400.  This high prevalence of congenital hypothyroidism could be a reason for the increased mental retardation in the district.
Further, poor diet, poor health practices, and unhygienic housing conditions may lead to mental retardation. These conditions are often associated with lower socioeconomic status and since 62% of our study population belongs to the lower middle class it could account for the increased prevalence of mental retardation.
The present study also revealed findings with a variation in the prevalence of mental retardation among the different population groups studied. What exactly accounts for this differential distribution across populations? Adverse social outcomes such as social disengagement, differences in lifestyle, differences in health awareness and health care delivery systems, differences in geographical distribution of genetic and environmental risks, and nutritional status may be the factors contributing to this difference. Further, this difference in mental retardation is similar to our findings on differential distribution of other disorders such as dementia. 
Probably the future research on mental retardation should focus on understanding the cause for its differential prevalence across populations.
| Conclusions|| |
In addition to the probable cause of congenital hypothyroidism, chromosomal and metabolic abnormalities maybe the reason for mental retardation. The study concludes with the hypothesis that the prevalence of mental retardation is differentially distributed geographically with socioeconomic factors being important predictors.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Reddy VB, Gupta A, Lohiya A, Kharya P. Mental health issues and challenges in India. IJSER 2013;3:1-3.
Durkin MS, Hasan ZM, Hasan KZ. Prevalence and correlates of mental retardation among children in Karachi, Pakistan. Am J Epidemiol 1998;147:281-8.
Panchani M. Causes of mental retardation: Environmental or genetic. IJLSER 2013;1:57-63.
Sooch SS, Ramalingaswami V. Preliminary report of an experiment in the Kangra valley for the prevention of Himalayan endemic goitre with iodized salt. Bull World Health Organ 1965;32:299-315.
Shrout PE, Newman SC. Design of two phase prevalence surveys of rare disorders. Biometrics 1989;45:549-55.
Govt. of India. Census 2011. Provisional Population Report. Office of the Registrar General and Census Commissioner India. Ministry of Home Affairs. Govt. of India: 2012. Available from: http://www.censusindia.gov.in
. [Last accessed on 2015 Jan 12].
Durkin MS, Wang W, Shrout PE, Zaman SS, Hasan ZM, Desai P, et al
. Evaluating a ten question screen for childhood disability: Reliability and internal structure in different cultures. J Clin Epidemiol 1995;48:657-66.
Sharma S, Raina SK, Bhardwaj AK, Chaudhary S, Kashyap V, Chander V. Socio demography of mental retardation: A community-based study from a goitre zone in rural sub-Himalayan India. J Neurosci Rural Pract 2015;6:165-9.
Durkin MS, Davidson LL, Hasan ZM, Hasan Z, Hauser WA, Khan N, et al
. Estimates of the prevalence of childhood seizure disorders in communities where professional sources are scarce: Results from Bangladesh, Jamaica and Pakistan. Pediatr Perinat Epidemiol 1992;6:166-80.
Durkin MS, Hasan ZM, Hasan KZ. The ten question screen for childhood disabilities: Its uses and limitations in Pakistan. J Epidemiol Community Health 1995;49:431-6.
Stein ZA, Durkin MS, Davidson LL, Desai P, Hasan ZM, Thorburn MJ, et al
. Guidelines for identifying children with mental retardation in community settings. In: Assessment of People with Mental Retardation. Geneva, Switzerland: World Health Organization; 1992. p. 12-41.
Thorndike RM, Hagen EP, Sattler JM. Stanford Binet Intelligence Scales. 4 th
ed. Chicago: Riverside Publishing Company; 1986.
American Association on Mental Retardation. Mental Retardation: Definition, Classification and Systems of Supports-Workbook. Washington DC: American Association on Mental Retardation; 1992.
Roeleveld N, Zielhuis GA, Gabreëls F. The prevalence of mental retardation: A critical review of recent literature. Dev Med Child Neurol 1997;39:125-32.
National Sample Survey Organization. Disabled Persons in India: NSS 58 th
Round. Report No. 485. New Delhi: Ministry of Statistics and Program Implementation, Government of India; 2002. Available from: http://mospi.nic.in/rept%20_%20pubn/485_final.pdf
. [Last accessed on 2015 Jul 7].
Raina SK, Razdan S, Nanda R. Prevalence of mental retardation among children in RS Pura town of Jammu and Kashmir. Ann Indian Acad Neurol 2012;15:23-6.
Ganguly HC. Epidemiological findings on prevalence of mental disorders in India. Indian J Psychiatry 2000;42:14-20.
Bijou SW, Browder JA, Danti A, Gerald PS, Hardman ML, Gail O, et al
. The Prevalence of Mental retardation. The National Association for Retarded Citizens - The Arc. Available from: www.thearc.org/who-we-are/history/segal-account
. [Last accessed on 2016 Jun 06].
Islam S, Durkin MS, Zaman SS. Socio economic status and the prevalence of mental retardation in Bangladesh. Ment Retard 1993;31:412-7.
Aggarwal S, Bogula VR, Mandal K, Kumar R, Phadke SR. Aetiological spectrum of mental retardation and developmental delay in India. Indian J Med Res 2012;136:436-44.
Drews CD, Yeargin-Allsopp M, Decouflé P, Murphy CC. Variation in the influence of selected sociodemographic risk factors for mental retardation. Am J Public Health 1995;85:329-34.
Murphy CC, Yeargin-Allsopp M, Decouflé P, Drews CD. The administrative prevalence of mental retardation in 10 year old children in metropolitan Atlanta, 1985 through 1987. Am J Public Health 1995;85:319-23.
Kapil U, Jain V, Kabra M, Pandey RM, Sareen N, Khenduja P. Prevalence of neonatal hypothyroidism in Kangra valley, Himachal Pradesh. Eur J Clin Nutr 2014;68:748-9.
Sundararaman PG. Neonatal thyroid dysfunction-lessons from Indian experience. Thyroid Res Pract 2013; 10(Suppl S1):7-8.
Raina SK, Raina S, Chander V, Grover A, Singh S, Bhardwaj A. Is dementia differentially distributed? A study on the prevalence of dementia in migrant, urban, rural, and tribal elderly population of Himalayan region in northern India. N Am J Med Sci 2014;6:172-7.
[Table 1], [Table 2], [Table 3], [Table 4]