CHAPTER TWO
2.3 Intellectual disability
2.3.4 Epidemiology of intellectual disability
Last (1995) defines epidemiology as ‗the study of the distribution and determinants of health- related states or events in specified populations and the application of the study to the control of health problems.‘ Harris (2006) confirms that epidemiology has a wider application beyond the traditional case finding and describing of the demography of a disorder, and therefore calls for future research to explore these other uses in the field of intellectual disability. He points out the importance of combining epidemiologic approaches with neurobiologic and psychosocial measures because epidemiology also studies the nature and scope of intellectual disability and its associated medical, behavioural, emotional, and psychiatric conditions. He further discloses that epidemiologic studies are capable of revealing individual developmental trajectories and the related risky, protective and resilient influences that shape those trajectories. Finally, he highlights the role of experimental epidemiologic approaches in the study of causes and factors that influence the course of the disorder and service needs.
Understanding the prevalence of intellectual disability is essential for planning and assessing interventions (Harris, 2006). Conversely, these estimates often vary widely due to the
45 heterogeneity of the condition as well as methods of case identification (Harris, 2006; Leonard &
Wen, 2002). Harris (2006) asserts that despite the wide variations in the reported prevalence of intellectual disabilities in various countries, they all point towards the fact that the prevalence is less than 1.0% in any population. However, an estimated prevalence of 3.0% has been adopted based on a statistical approach and an IQ of below 70. According to Leonard and Wen (2002), the large differences in prevalence estimates may partially be linked to lack of consensus on the criteria for defining intellectual disability and methods of case finding, which have great implications for epidemiological research. Researchers are of the opinion that apart from the general population prevalence of intellectual disability, it is critical to also know the prevalence of specific intellectual disabilities based on their causes (Harris, 2006; Holtzman, 2003). In addition, Harris (2006) advises that population studies should be aware of the various terms that have been used to describe intellectual disability and published studies should criticise the definitions used in case finding.
Basically, at least three approaches of defining intellectual disability have been identified in research: statistical models; pathological models; and social systems models (Harris, 2006). He asserts that the statistical model which uses psychometric tests and the pathological model that places emphasis on adaptive skills offer pragmatic definitions, and combining the two generates the currently acceptable definition of intellectual disability for research purposes. This approach presents a broader and more meaningful picture of intellectual disability in the population (Leonard & Wen, 2002).
However, the existence of criticisms of the assumptions and variations within each of these models presents other challenges. The statistical model, by using an IQ score two standard deviations below the mean, assumes a normal distribution and hence a continuum of cognitive abilities (Harris, 2006; Leonard & Wen, 2002). In contrast, variations in cognitive profile and associated conditions complicate assessment and categorisation (Harris, 2006). Furthermore, the AAMR (AAIDD) measure of sub-average intellectual functioning IQ score of approximately 70-75 or below has come under criticism. MacMillan, Gresham, and Siperstein (1995) argue that AAMR‘s (AAIDD) definition is too imprecise to be useful in research and should rather be
46 reserved for advocacy purposes because it is capable of adding 2.8% of the population with IQs between 71 and 75 to the population of intellectually disabled.
Some studies prefer to use only a statistical model, partly due to a lack of totally objective or standardised adaptive behaviour measures in different socio-economic and cultural environments (Leonard & Wen, 2002). Although this may be justifiable, Leonard & Wen (2002) report the authors‘ acknowledgement that there is a high probability of including individuals who otherwise would not have been classified as having intellectual disability because of an absence of deficiency in adaptive skills.
The social system model is most commonly used by schools to label children as intellectually disabled at school entry (Harris, 2006). Harris (2006) further points out that such children (especially those in the mild category), however, may not fit into the classification before and after school if they can function adequately and have sufficient physical and social skills to live and work independently in society. Another methodological factor that may influence prevalence is ascertaining methods. According to Leonard and Wen (2002), ‗cases should be ascertained from the entire populations and not limited to individuals receiving selected specialty services (e.g. hospital-based services) or living in institutions‘.
Furthermore, Harris (2006), in what seems like an insight from the developed world, suggests other factors that may affect the prevalence of intellectual disability. He mentions programmes such as normalisation, mainstreaming and improved interventions for previously disadvantaged individuals. In addition, he acknowledges the positive impact of poverty reduction, improved nutrition, early intervention and advancement in medical diagnoses on the prevalence of intellectual disability. Similarly, greater availability of genetic counselling, prenatal diagnosis, abortion services for high-risk pregnancies, postnatal dietary/hormonal treatments for inborn errors and improved obstetrical techniques are also mentioned. An increase in the life span of affected persons through improved quality of life has also affected prevalence. Nevertheless, improvements in care for premature infants are identified as a cause of intellectual impairment in low birth weight infants who survive.
47 A number of demographic factors have also been identified as affecting prevalence. These include age, gender, socio-economic level, and race (Leonard & Wen, 2002). Harris (2006) and Leonard & Wen (2002) affirm that age-specific rates of intellectual disability differ in a population. To support this observation, Harris (2006) relates that ‗most surveys show an increase in prevalence from the preschool years (0 to 4) to middle childhood (5 to 12)‘. In contrast, Leonard and Wen (2002) argue that this may not necessarily mean that there are actual variations in prevalence in a population but rather, a reflection of differences in case identification. Most children with severe intellectual disability may have been identified prior to school (Harris, 2006), whereas those functioning in the mild category may only be recognised at that time (Harris, 2006; Leonard & Wen, 2002). Increase in cognitive demands made by the school system and adaptive difficulties related to social judgment and behaviour control may increase the prevalence during the teen years (Harris, 2006). It is also possible for population prevalence of mild intellectual impairment in young adulthood to drop because they have been able to adapt to the demands of the society with time (Harris, 2006; Leonard & Wen, 2002).
Finally, it has been postulated that the decrease in prevalence seen in older persons is as a result of the shorter life span of persons with intellectual disability, as well as reduced demands on them from vocational programmes (Harris, 2006; Leonard & Wen, 2002).
Commenting on the reports of higher prevalence of intellectual disability among males than females, Harris (2006) links this to higher prevalence of congenital abnormalities, premature birth, neonatal death, stillbirth, and X-linked disorders in males. Also, he notes that aggressive behaviour in boys is likely to draw the attention of authorities, thus leading to more frequent diagnosis than in girls. Conversely, other studies did not confirm this, especially when age and the severity of intellectual disability were considered (Harris, 2006; Leonard & Wen, 2002).
In addition, socio-economic level is a critical factor in mild intellectual disability due to differences in sensory and psychosocial factors like poor living conditions, overcrowding, and lack of educational opportunities (Harris, 2006; Leonard & Wen, 2002). Both studies also claim that the observed higher prevalence of mild intellectual disability among some racial minorities is linked to socio-economic level and not to race. Therefore, Leonard and Wen (2002) emphasise the importance of methodological issues and potential confounders, including case definitions,
48 study designs, demographic composition of the study population, maternal factors, early intervention efforts and other socio-economic and cultural factors, in assessing how racial differences may affect prevalence.