We reported previously that the point prevalence of high DD was about 18% of patients in our diverse community sample, and that high DD, once it occurs, is a relatively persistent condition (3). In the current study we found that an additional 17.2% of patients without high DD at initial assessment reported high DD during the following 18 months. We identified a core group of variables that, across analyses, were consistently predictive of +DD, with ROC statistics indicating good discriminability between groups: being female, having MDD during the previous year, experiencing more NLE and more chronic stress, having high numbers of complications, and having poor diet and low exercise.
Of interest is that, even with the relatively small sample size (N=332), the ORs for general patient characteristics, biological variables and behavioural variables remain stable across all analyses. This, along with a lack of multicollinearity, suggests that their associations with +DD are relatively independent of the other variables that are included. Also of note, both NLE and chronic stress reached or approached statistical significance in all three models and across all analyses: in each case, high NLE and more chronic stress, unrelated to diabetes or its management, are associated with subsequent +DD. It appears that the stresses associated with having significant complications, the demands of NLE and non disease-related chronic stress, the difficulties of effectively managing diet and exercise, and the burdens posed by a recent episode of MDD each contribute independently to +DD.
Similar patterns emerge upon review of the exploratory analyses of interactions, such that both non diabetes-related stressors (NLE) and diabetes-related stressors (HbA1c, complications) magnify the effect of other conditions on +DD. For example, NLE increases the negative effects of both higher HbA1c and higher complications on +DD, such that NLE has a greater negative effect for patients who experience a more severe disorder. Likewise, even though male patients and those without recent MDD have a somewhat lower probability of +DD over time than female patients and those with MDD, high NLE appears to neutralize these differences. Under conditions of high NLE, the probabilities of becoming distressed increase significantly among male patients and those without MDD. In this sense, stressors from both diabetes-related and non health-related areas of life contribute to predicting +DD.
These findings suggest that not only do broader life context issues influence diabetes and its management directly, they may also interact with diabetes-specific factors, such as HbA1c
and complications, to affect +DD. Although many clinicians have become increasingly aware of the influence of diabetes-related distress and depressive affect on self-management and diabetes outcomes 11
, less attention has been devoted to other equally powerful stressors that occur within the patient’s broader life context that can also affect diabetes. For example, in a large primary care sample, Albright, et al. 7
showed that personal stress and family context, among others, are significantly associated with diabetes self-care activities; and several daily assessment studies have indicated that patient reports of stressful days, unrelated to diabetes management, are linked to subsequent changes in average blood glucose levels 5, 14
. Thus, current levels of financial, work, family and other event-based and chronic life stressors should be assessed and responded to when designing programs of care. For example, a period of significant chronic or NLE stress may not be the best time to introduce major changes in physical activity, diet, or introduction of insulin therapy. Furthermore, it may be important to refer patients to services that might help reduce the impact of these stressors before they affect diabetes management. The list of predictors of +DD above provide rough areas for screening those patients with current low DD who are at risk for high DD in the near future, with special emphasis on women, and those with high NLE. NLE may be especially important in this regard because of its potential for magnifying the impact of diabetes characteristics, such as HbA1c
or complications on subsequent distress.
There are several limitations to these findings. First, we systematically explored a relatively large number of predictors with a sample of modest size. Although we evaluated potential problems by assessing the ORs at the univariate level, employed a step-wise procedure, re-evaluated with backward elimination, and tested for multicollinearity to assess for instability of results, our findings, especially the interaction term data, will require replication. Second, we did not explore the potentially protective effects of patient traits and social supports that could serve to buffer the effects of stress on +DD. Third, we explored only a relatively narrow range of potential predictors. Other, unevaluated patient characteristics may be equally predictive.
Despite these limitations, the current study shows that, over and above those who are already distressed about diabetes at any one point in time (~19%), an additional 17% of type 2 diabetic patients become high DD over the succeeding 18 months. We identified several significant, independent predictors of subsequent high DD that can be used for patient screening to identify this high risk patient cohort. Given the impact of high DD on diabetes behavioural and biological indicators, the findings suggest the usefulness of regularly appraising both current life and disease-related stressors in clinical care.