Identifying Individuals With Intellectual Disability Within a Population Study

Background Much remains unknown about the longitudinal health and well-being of individuals with intellectual disability (ID); thus, new methods to identify those with ID within nationally representative population studies are critical for harnessing these data sets to generate new knowledge. Objective Our objective was to describe the development of a new method for identifying individuals with ID within large, population-level studies not targeted on ID. Methods We used a secondary analysis of the de-identified, restricted-use National Longitudinal Study of Adolescent to Adult Health (Add Health) database representing 20,745 adolescents to develop a method for identifying individuals who meet the criteria of ID. The three criteria of ID (intellectual functioning, adaptive functioning, and disability originating during the developmental period) were derived from the definitions of ID used by the American Psychiatric Association and the American Association on Intellectual and Developmental Disabilities. The ID Indicator was developed from the variables indicative of intellectual and adaptive functioning limitations included in the Add Health database from Waves I to III. Results This method identified 441 adolescents who met criteria of ID and had sampling weights. At Wave I, the mean age of this subsample of adolescents with ID was 16.1 years. About half of the adolescents were male and from minority racial groups. Their parents were predominately female, were married, had less than a high school education, and had a median age of 41.62 years. The adolescents' mean maximum abridged Peabody Picture Vocabulary Test standardized score was 69.6, and all demonstrated at least one adaptive functioning limitation. Discussion This study demonstrates the development of a data-driven method to identify individuals with ID using commonly available data elements in nationally representative population data sets. By utilizing this method, researchers can leverage existing rich data sets holding potential for answering research questions, guiding policy, and informing interventions to improve the health of the ID population.