UC Irvine

Objective: To study children’s self-reporting health measures, as obtained from the Child Health Ratings Inventories (CHRIs) tool, according to race/ethnicity and/or socioeconomic status in order to understand and better improve the health quality of the pediatric patient population.

Patients and Methods: Longitudinal data was collected from a larger PCORI study developing and testing an animated computer survey, termed CHRIs, for the measurement of health amongst children. Pediatric surgical patients (4-12 years old) were surveyed with the CHRIs tool at three specific timepoints (pre-surgery, 2-days post, and 7-days post-surgery) to better understand their health status before and after their surgical procedure. The surveys inquired into the functional capacity or quality of life of the pediatric patients, who were read survey questions and then were able to select from survey responses represented as animations that illustrate the various possible health statuses. An aggregated dataset at the baseline timepoint, along with demographic information obtained from surveying of accompanying parents, were used for the analyses. The primary variables of education and annual income were used to create a composite variable that then was analyzed as a binary grouping variable called socioeconomic status (SES). The racial/ethnic profile of the pediatric population was examined in a binary manner as well -Hispanic or Non-Hispanic. From which, a composite variable examining both race/ethnicity and SES was developed and utilized in comprehending how children’s self-reported health measures may vary based on such.

Results: SES was distinguished as low or high depending on the respective education and income metrics reported from the pediatric patients’ guardians. Race/ethnicity was differentiated as either Hispanic or Non-Hispanic, in which there were no identified confounding variables in choosing to group all racial/ethnic groups, excluding Hispanics, as a mixed categorical variable. In total, all racial/ethnic groups, other than Hispanics, represented a lower sample size as compared to the Hispanic only group, and no major differences were observed when comparing Non-Hispanic White only to the mixed grouping of Non-Hispanics, which was inclusive of Whites, Asians, and other minorities. To maintain the dataset with as much of the patient population captured, the holistic Non-Hispanic group was utilized for racial/ethnic comparisons against Hispanics. Overall, pediatric patients who identified as either Low SES or Hispanic were more likely to report lower CHRIs health measures scores, thus poorer health, than their High SES or Non-Hispanic counterparts. Further, pediatric patients, who were Low SES and Hispanic, tended to report the worst health as compared to those who were Low SES Non-Hispanic, High SES Hispanic, or High SES Non-Hispanic.

Conclusions: There is a demonstrated relationship between race/ethnicity and SES, in which the two variables intersect and impact one another. Trends suggest that being Low SES or Hispanic results in poorer health than the counterparts of being High SES or Non-Hispanic. When examining both SES and race/ethnicity together, being Hispanic and of Low SES suggests lower health reporting. The analyses of race/ethnicity and SES with regards to child’s reporting of health demonstrates how considering the context and the demographic profile of patients through categorical variables, like race/ethnicity and SES, lend to better understanding of their health status. There is utility in self-reporting mechanisms, like the CHRIs tool, in which direct reporting from vulnerable populations, such as children, can allow for more targeted health diagnoses and better treatment plans.