LINK TO RESEARCH
Journal of Pediatric Nursing
Jennifer McGuire Hitt 1 ,
Pedro Velasquez-Mieyer 2 ,
Claudia Neira 2 ,
Patricia Cowan 3
We sought to examine the correlation between variables and A1C levels to
determine if prediction modeling could be used in the screening and
diagnosis of diabetes and prediabetes in youth. We also sought to test
relationships between A1C levels to insulin sensitivity indices and β-cell
Design and methods: We performed a retrospective review of 904 medical records from youth
deemed at-risk for the disease. We performed Pearson correlation, multiple
regression, and simple regression testing to determine the relationship
between variables and A1C levels. In addition, we performed Pearson
correlation testing on insulin sensitivity indices and β-cell function
indices to determine the strength of correlation to A1C levels.
Results: Statistical analysis did not show a strong relationship between the
variables tested and the A1C. When racial and ethnic groups were tested
together, the results from African American participants resulted in bias
estimates, and as a result, a statistical model for the entire sample could
not be performed. Results indicate that A1C is correlated with all β-cell
function proxy measurements and correlated to the corrected insulin level
at 30minutes, but not the fasting insulin or insulinogenic index.
Discussion: The results from this study underline the multi-dimensional causes of
diabetes and prediabetes and further stress the difficulties in predicting
the diseases. The causes of diabetes and prediabetes are multifaceted,
often individualized, and often difficult to ascertain.
Practice implications: Clinicians should continue to examine a variety of variables prior to
determining the need for diabetes diagnostic testing.
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