Abstract
BACKGROUND: Sickness-related absences are of particular importance both in the German armed forces and in the civilian sector. THE AIM OF THIS STUDY: was to analyze the incidence of sick leave among soldiers in comparison to the working population covered by the statutory health insurance (SHI) system. METHOD: According to the systematics of the SHI, the key figures on incapacity to work in the period 2008-2018 are calculated in an age- and gender-standardized manner. Likewise, a list of the TOP 20 ICD-10 diagnoses in relation to incapacity to work was determined, and their average annual rates of change were calculated for trend analysis. RESULTS: The annual rate of sick leave among soldiers was between 1.5 and 2.3%, which was lower than that of the SHI (3.1 to 5.0%). The duration of illness (sick days per case) among soldiers was between 9.0-15.6 days per year, compared with 10.9-14.4 days in the SHI system. The sickness frequency (cases per 100 persons) was lower among soldiers (48.2-75.0 cases) than in the SHI (96.8-131.0 cases). Most days of absence among soldiers were due to "respiratory infections (J06)" with 13.2%, "stress reactions (F43)" with 8.7%, "other infectious gastroenteritis and colitis (A09)" with 6.5%, "back pain (M54)" with 4.4% and "depressive episode (F32)" with 4.0% of all days of absence and were comparable to the values in SHI. "Depressive episode (F32)", "injuries (T14)", sreactions (F43)", "respiratory infections (J06)" and "pregnancy complaints (O26)" showed the highest rates of increase of+6.1% to+3.6% of days off work. CONCLUSION: For the first time, it was possible to compare the sickness rate of soldiers with that of the general population in Germany, which may also provide indications for further measures for primary, secondary and tertiary prevention. The lower sickness rate among soldiers compared with the general population is mainly due to a lower incidence of illness, with a similar duration and pattern of illness, but with an overall upward trend. The ICD-10 diagnoses "Depressive episode (F32)," "injuries (T14)," "stress reactions (F43)," "acute upper respiratory tract infections (J06)" and "pregnancy complaints (O26)," which are increasing at an above-average rate in relation to the number of days absent, require further analysis. This approach seems promising, for example, to generate hypotheses and ideas for further improvement of health care.