A surge in the incidence of obesity in children has led to increased interest in identifying intervention and prevention measures. Accordingly, Curtin et al. (2010) performed a study to determine the incidence of obesity in autistic kids. The incidence rates were compared to those of children without autism. The study used secondary data from the National Survey of Children’s Health (NSCH). The data collection method used in the study was telephone interviews. Samples were obtained using a random sampling of households across the fifty states. Curtin et al. (2010) determined that 30.4% of autistic kids were obese, while only 23.6% of neurotypical kids had obesity. The study recommended further research to identify the factors contributing to the higher obesity prevalence in children with autism.
Research Design
Curtin et al. (2010) used secondary data analysis to determine the incidence of obesity in autistic kids. Random sampling was used to identify suitable study participants. 85,272 children were selected from the original 102,353 samples. Using a telephone interview, trained interviewers asked the respondents several questions about the child’s physical and psychological health. The child’s age was used as the inclusion criteria, whereby only children aged between three and seventeen were included in the study. A previous diagnosis by a healthcare professional determined the presence of autism. Data about the children’s height and weight were also collected during the interview to calculate body mass index (BMI). Sampling weights outlines in the NSCH survey were used to generate population-based estimates. A design-adjusted Chi-Square test was used to compare obesity rates in kids with and without autism. Logical regression analysis was applied to determine the odds ratio for autism-related obesity (Curtin et al., 2010).
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Explanation of the Secondary Dataset
Secondary data was collected from the NSCH. The survey ran from January 2003 to July 2004. The Centers for Disease Control and Prevention (CDC) sponsored the survey. The survey aimed to evaluate the physical and psychological health of kids aged between zero and seventeen. The population sample comprised of typically developing children and those with special needs. A telephone interviewing system was used to collect data from a randomly selected sample. Random sampling was performed by randomly digit-dialing households. Selected households had to have one or more children under eighteen. One child was randomly chosen from each household to be the focus of the survey. The dataset provided children’s information about their geographical location, race, language, family structure, height, and weight (Curtin et al., 2010).
Study Variables
The independent variable used in the study was the formal diagnosis of autism, a developmental disorder, by a health professional. The dependent variable used in the study was weight status (obesity), which was determined by calculating the BMI from the weight and height information collected from the interviews and compared to the data provided in the NSCH.
Critical Evaluation
The secondary data analysis was a viable study design since it utilized limited time and resources. Individually collecting nationally representative data would have been very expensive for the study. Therefore, using a secondary data set provided a cost-effective and convenient option. Additionally, the NSCH is government-sponsored and subjected to high research standards ensuring that high-quality, large, and accurate datasets are available. Therefore, it is appropriate for the study. The secondary data set is also nationally representative, enhancing the study results' validity and generalizability (Johnston, 2017). Using a telephone interview to collect data about children’s height and weight was inappropriate since most parents were not certain about these measurements and provided estimates. Others were unable to respond (Curtin et al., 2010). The data collection methods adversely affected the accuracy of the study results.
References
Curtin, C., Anderson, S. E., Must, A., & Bandini, L. (2010). The prevalence of obesity in children with autism: A secondary data analysis using nationally representative data from the National Survey of Children’s Health. BMC Pediatrics 10 (1), 11. https://doi.org/10.1186/1471-2431-10-11.
Johnston, M. P. (2017). Secondary data analysis: A method of which the time has come. Qualitative and Quantitative Methods in Libraries , 3 (3), 619-626. http://www.qqml-journal.net/index.php/qqml/article/view/169
