Prior work has documented, that individuals with diabetes and depression or psychological distress show a higher utilization of health care (e.g.7). However, previous studies have either investigated the associations in cross-sectional designs, focused on the influence of cost as a single factor of health care utilization, or focused on depression symptoms only (e.g.7,8). Moreover, no study has investigated the impact of diabetes-related distress on future health care costs and future lost workdays. In our study, we used records from a large German SHI so we could capture participants’ total health care costs and lost workdays for a full year after the survey. Hence, we were able to investigate the factors associated with the future costs of health care and lost workdays in one data set.
As expected, we found that depression symptoms in individuals with diabetes were associated with significantly higher health care costs in the following year. Depression symptoms tended to also predict lost workdays in the following year, but the differences were not significant. In the case of diabetes-related distress, surprisingly, it tended to be associated with lower future health care costs and a lower risk of losing workdays in individuals with diabetes. However, this was the case only in the regression models, and the results were not significant.
Our findings extend results on future health care costs by Simon et al.2, Gilmer et al.10, Huang et al.5, Vamos et al.14, and Ciechanowski et al.9, in confirming that depression symptoms may act as a significant independent predictor of health care costs. Respondents with symptoms of major depression had almost 50% higher total health care costs compared with respondents without symptoms of major depression in the year after the survey. This is in line with findings from Simon et al.2, who found that health care costs were approximately 70% higher for individuals with symptoms of major depression compared with those without any symptoms of depression for the six months after the survey. Additionally, it seems that individuals with diabetes and depression symptoms incur higher costs, irrespective of the health care system in which they are receiving their care. The study by Simon et al.2 was carried out in the US, which has a mainly private market, whereas our results were based on data from a statutory health insurance system in Germany.
We found that respondents with high diabetes-related distress tended to have lower future health care costs than respondents without high diabetes-related distress, but this result was not significant. At first glance, this seems somewhat surprising as one could assume that individuals who experience high distress are more likely to be sick and would therefore incur higher health care costs. However, one reason for our finding might be that individuals who are highly engaged in their diabetes self-management experience also have higher diabetes-related distress and—as a consequence—experience fewer short- and long-term complications and produce lower health care costs. Furthermore, they might also feel more burdened by the disease. This would be in line with previous findings, in which comorbidities were shown to be a strong predictor of future health care costs5, independent of depression symptoms or distress. Moreover, our results on diabetes-related distress and costs seem to be reversible for higher costs, and therefore, different results are possible, depending on the statistical methods. For instance, we observed 19% lower costs for respondents with high diabetes-related distress in the regression analysis after adjusting for several covariates (see Table 3), even though a non-parametric comparison (see Table 2) showed that respondents with high diabetes-related distress had higher costs. However, in the sensitivity analysis, which included only respondents with costs up to 10,000 €, we found 14% higher costs among those with high diabetes-related distress (see Suppl Appendix 2), a finding that is in line with the results of the non-parametric comparison. In the sensitivity analysis, we found that the risk of lost workdays in the following year in individuals with symptoms of major depression tended to be higher compared with individuals with no symptoms of major depression. This result is in line with previous findings in cross-sectional designs11,13. However, for diabetes-related distress, our data point in the opposite direction: high diabetes-related distress tended to predict a lower risk of lost workdays in the following year. Considering the mean age of our sample (66.9 years), one could argue that those who are still working are healthier than those who are not working and are probably more engaged in their diabetes self-management and thus experience higher diabetes-related distress; as a consequence, they have fewer short- and long-term complications, which in turn lead to fewer lost workdays.
Strengths and limitations
A number of limitations should be considered when interpreting the results. First, only individuals from one SHI could participate in the study, which might influence the results, as the populations insured with the different SHIs in Germany differ considerably39. The results are therefore not representative of the German population with diabetes at large. Second, to assess depression symptoms, we used self-report questionnaires; nevertheless, the gold standard for assessing depression is the clinical interview. Therefore, we cannot conclude that all respondents identified with depression symptoms would have been diagnosed with major depression in an interview with a clinician. However, the PHQ-9 provides a standardized measure of the DSM-IV criteria for major depression and has been found to discriminate well between individuals with and without major depression (the area under the curve in a ROC analysis was 0.95 in diagnosing major depression)31. The reported prevalence of 5.7% is indeed low however within the range reported by a recent systematic review where prevalence rates among patients with diabetes ranged from 1.8 to 88.6%40. The authors found that prevalence estimates based on clinical samples were generally higher than prevalence estimates of community samples possibly due to differences in participant characteristics and a greater severity of depression within clinic settings. Moreover, they found the lowest prevalence based on the PHQ-9 with a cut-off ≥ 10 in a Chinese sample41. Thus, our prevalence estimates seem to be low however within the range of expected outcomes. Third, depending on the effect size, the number of employed respondents might not have provided enough power to detect significant differences in the analysis of the risk of lost workdays.
On the other hand, the study has several strengths. The DiaDec study had a reasonably high response rate (51%) for a survey-based study, and the data set was rather large and thus allowed for robust estimates. Even though antihyperglycemic medication, health care utilization, and medication utilization were higher among people who responded to the survey than those who did not, there was no difference between the two groups regarding previous diagnosis of depression30. Moreover, our design allowed us to link longitudinal SHI data with the survey data.
Combining information about health care costs and lost workdays in one data set provided evidence of the impact of depression symptoms and diabetes-related distress. Many health care plans focus on glycemic control to reduce costs. Our results show that more attention should especially be paid to individuals with diabetes and depression symptoms, as not only their present (e.g.7,8,11,42) but also their future costs and losses in productivity are major issues. A successful treatment of depression among individuals with diabetes should be a major goal in disease management programs; these may include, for example, psychotherapy (individual, group-based or online), pharmacological treatment, improved diabetes self-management, regular physical activity, or stress reduction techniques43,44,45. This is of high clinical relevance and could contribute to a massive reduction in health care costs and is thus of great importance to health care professionals and policy makers. However, further research is necessary to demonstrate whether these results hold true in other samples as well.
In summary, our results for depression symptoms and diabetes-related distress point in opposite directions. Although the concepts of depression and diabetes-related distress may overlap to some extent, our results indicate that, in the case of health care costs and lost workdays, they probably do not.
To our knowledge, this is the first study to compare future health care costs and lost workdays for individuals with diabetes reporting major depression symptoms or high diabetes-related distress. Further studies are needed to confirm whether our findings hold true in other samples as well.