ObjectiveIn large cohort studies comorbidities are usually self-reported by the patients. This way to collect health information only represents conditions known, memorized and openly reported by the patients. Several studies addressed the relationship between self-reported comorbidities and medical records or pharmacy data, but none of them provided a structured, documented method of evaluation. We thus developed a detailed procedure to compare self-reported comorbidities with information on comorbidities derived from medication inspection. This was applied to the data of the German COPD cohort COSYCONET.MethodsApproach I was based solely on ICD10-Codes for the diseases and the indications of medications. To overcome the limitations due to potential non-specificity of medications, Approach II was developed using more detailed information, such as ATC-Codes specific for one disease. The relationship between reported comorbidities and medication was expressed by a four-level concordance score.ResultsApproaches I and II demonstrated that the patterns of concordance scores markedly differed between comorbidities in the COSYCONET data. On average, Approach I resulted in more than 50% concordance of all reported diseases to at least one medication. The more specific Approach II showed larger differences in the matching with medications, due to large differences in the disease-specificity of drugs. The highest concordance was achieved for diabetes and three combined cardiovascular disorders, while it was substantial for dyslipidemia and hyperuricemia, and low for asthma.ConclusionBoth approaches represent feasible strategies to confirm self-reported diagnoses via medication. Approach I covers a broad spectrum of diseases and medications but is limited regarding disease-specificity. Approach II uses the information from medications specific for a single disease and therefore can reach higher concordance scores. The strategies described in a detailed and reproducible manner are generally applicable in large studies and might be useful to extract as much information as possible from the available data.

Psychological distress is associated with the psychosocial work environment in Andean underground miners. Interventions in mining populations should take the psychosocial work environment into account.

ObjectivesWe aimed to prospectively study the association between normalised difference vegetation index (NDVI) as a measure of greenness around homes and occupational stress.SettingA population-based cohort in Munich and Dresden cities was followed from age 16–18 years to age 20–23 years (n=1632).ParticipantsAt baseline, all participants attended high-school while at follow-up some had started working and others studying at university. At baseline and in each follow-up, we assigned NDVI based on participants’ residential geocoded addresses and categorised it by quartiles.Outcome measuresSchool-related, university-related or job-related self-reported chronic stress was assessed at the two follow-ups by the Trier Scale for Assessment of Chronic Stress using work discontent and work overload as outcomes. We modelled the association employing ordinal generalised estimating equations model accounting for changes in sociodemographics, non-job-related stress, job history and environmental covariates. Stratified analysis by each city was performed.ResultsNVDI at baseline was higher for participants from Dresden (median=0.36; IQR 0.31–0.41) than Munich (0.31; 0.26–0.34). At follow-up, it decreased only for participants in Dresden (0.34; 0.30–0.40). Higher greenness (quartile 4 vs quartile 1) was associated with less work discontent (OR 0.89; 95% CI 0.80 to 0.99) and less work overload (OR 0.87; 95% CI 0.78 to 0.96). In stratified analyses, results were more consistent for Munich than for Dresden.ConclusionsOur results suggest that residential green spaces, using the vegetation index as a proxy for exposure, are inversely associated with two types of job-related chronic stress in German young adults transitioning from school to university or working life.

In a town located in a desert area of Northern Chile, gold and copper open-pit mining is carried out involving explosive processes. These processes are associated with increased dust exposure, which might affect children’s respiratory health. Therefore, we aimed to quantify the causal attributable risk of living close to the mines on asthma or allergic rhinoconjunctivitis risk burden in children. Data on the prevalence of respiratory diseases and potential confounders were available from a cross-sectional survey carried out in 2009 among 288 (response: 69%) children living in the community. The proximity of the children’s home addresses to the local gold and copper mine was calculated using geographical positioning systems. We applied targeted maximum likelihood estimation to obtain the causal attributable risk (CAR) for asthma, rhinoconjunctivitis and both outcomes combined. Children living more than the first quartile away from the mines were used as the unexposed group. Based on the estimated CAR, a hypothetical intervention in which all children lived at least one quartile away from the copper mine would decrease the risk of rhinoconjunctivitis by 4.7 percentage points (CAR: −4.7; 95% confidence interval (95% CI): −8.4; −0.11); and 4.2 percentage points (CAR: −4.2; 95% CI: −7.9;−0.05) for both outcomes combined. Overall, our results suggest that a hypothetical intervention intended to increase the distance between the place of residence of the highest exposed children would reduce the prevalence of respiratory disease in the community by around four percentage points. This approach could help local policymakers in the development of efficient public health strategies.