Introduction: Older adults who have diabetes vary widely in terms of comorbid conditions; these conditions help determine the risks and benefits of intensive glycemic control. Not all people benefit from intensive glycemic control. The objective of this study was to classify by comorbid conditions older American adults who have diabetes to identify those who are less likely to benefit from intensive glycemic control.
Methods: We used latent class analysis to identify subgroups of a nationally representative sample of community-dwelling older adults (aged 57-85 y) who have diabetes (n = 750). The subgroups were classified according to 14 comorbid conditions prevalent in the older population. Using the Akaike Information Criterion, the Bayesian Information Criterion (BIC), the sample-size adjusted BIC, and the χ(2) goodness-of-fit statistic, we assessed model fit.
Results: We found 3 distinct subgroups. Class 1 (63% of the sample) had the lowest probabilities for most conditions. Class 2 (29% of the sample) had the highest probabilities of cancer, incontinence, and kidney disease. Class 3 (9% of the sample) had the highest probabilities (>90%) of congestive heart failure and myocardial infarction. Class 1 had only 0, 1, or 2 comorbid conditions, and both class 2 and class 3 had 6 or more comorbid conditions. The 5-year death rates for class 2 (17%) and class 3 (33%) were higher than the rate for class 1 (9%).
Conclusion: Older adults who have diabetes, cardiovascular disease, and 6 or more comorbid conditions may represent a subgroup of older adults who are less likely to benefit from intensive glycemic control.