A comparison between the self-report of chronic cardiovascular diseases with health insurance data: insights from the population-based LIFE-Adult study
Abstract Background Self-reporting is a common approach in observational epidemiological studies. However, information can be biased by several causes and can, therefore, affect the outcomes of the investigations. This analysis aimed to evaluate the agreement between self-reported data from a popula...
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BMC
2025-05-01
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| Series: | Archives of Public Health |
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| Online Access: | https://doi.org/10.1186/s13690-025-01606-3 |
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| author | Samira Zeynalova Peter Worringen Stefan Bassler Anja Martin Katrin Czech Lars Greulich Matthias Reusche Ute Enders Nigar Reyes Maryam Yahiaoui-Doktor Matthias Collier Markus Loeffler Tina Stegmann |
| author_facet | Samira Zeynalova Peter Worringen Stefan Bassler Anja Martin Katrin Czech Lars Greulich Matthias Reusche Ute Enders Nigar Reyes Maryam Yahiaoui-Doktor Matthias Collier Markus Loeffler Tina Stegmann |
| author_sort | Samira Zeynalova |
| collection | DOAJ |
| description | Abstract Background Self-reporting is a common approach in observational epidemiological studies. However, information can be biased by several causes and can, therefore, affect the outcomes of the investigations. This analysis aimed to evaluate the agreement between self-reported data from a population-based cohort study with data from two large German health insurance companies. Methods Participants with available self-reported diagnoses of a history of stroke, atrial fibrillation (AF), heart failure (HF), and myocardial infarction (MI) from the baseline and the follow-up (after six years) surveys of the prospective population-based LIFE-Adult study were included in this study. Two health insurance companies provided ICD-10-GM codes. The agreement between the self-reports and health insurance data (HID) was examined by calculating sensitivity, specificity, Cohen`s Kappa, positive and negative predictive values. We used multivariable logistic regression models to examine whether odds ratios (OR) for the association between risk factors and the certain disease changed, depending on whether self-reports or HID was used as the dependent variable. Results One thousand seven hundred eighty four individuals with complete data were included in this interim analysis. Mean age was 58 (SD±12) years and 984 (55%) were female. 52 (2.9%) subjects reported a history of stroke, 99 (5.6%) AF, 63 (3.5%) HF, and 46 (2.6%) MI. Compared with the HID, a high specificity was found for all four diagnoses (stroke: 99% [95% CI 99.3-99.9]; AF: 99% [95% CI 98.1-99.2], HF: 98% [95% CI 97.6-98.9], and MI: 99% [95% CI 98.9-99.7]). Sensitivity ranged from 58% (95% CI 47.4-69.5) for stroke over 61% (95% CI 48.8-74.0) for MI, to 65% (95% CI 56.6-73.9) for AF. Sensitivity in HF was the lowest (20% [95% CI 14.4-26.5]). Conclusion The use of German health insurance data is a feasible method for verifying population-based self-reported diagnoses. The sensitivity varied among the self-reported diseases compared with the health insurance data, whereas the specificity was continuously high. The verification of self-reported diagnoses using health insurance data as an additional data source may be considered in future population-based assessments to reduce misclassification error of self-reported data. |
| format | Article |
| id | doaj-art-5b4c3ebb90bd4e71bffe753f9954f168 |
| institution | OA Journals |
| issn | 2049-3258 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | BMC |
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| series | Archives of Public Health |
| spelling | doaj-art-5b4c3ebb90bd4e71bffe753f9954f1682025-08-20T01:49:36ZengBMCArchives of Public Health2049-32582025-05-0183111010.1186/s13690-025-01606-3A comparison between the self-report of chronic cardiovascular diseases with health insurance data: insights from the population-based LIFE-Adult studySamira Zeynalova0Peter Worringen1Stefan Bassler2Anja Martin3Katrin Czech4Lars Greulich5Matthias Reusche6Ute Enders7Nigar Reyes8Maryam Yahiaoui-Doktor9Matthias Collier10Markus Loeffler11Tina Stegmann12Institute for Medical Informatics, Statistics and Epidemiology (IMISE), Leipzig UniversityInstitute for Medical Informatics, Statistics and Epidemiology (IMISE), Leipzig UniversityAOK PLUS DEIKK classicIKK classicAOK PLUS DEInstitute for Medical Informatics, Statistics and Epidemiology (IMISE), Leipzig UniversityInstitute for Medical Informatics, Statistics and Epidemiology (IMISE), Leipzig UniversityInstitute for Medical Informatics, Statistics and Epidemiology (IMISE), Leipzig UniversityInstitute for Medical Informatics, Statistics and Epidemiology (IMISE), Leipzig UniversityThe Clinical Trial Centre (ZKS) Leipzig, Leipzig UniversityInstitute for Medical Informatics, Statistics and Epidemiology (IMISE), Leipzig UniversityDepartment of Cardiology, Leipzig University HospitalAbstract Background Self-reporting is a common approach in observational epidemiological studies. However, information can be biased by several causes and can, therefore, affect the outcomes of the investigations. This analysis aimed to evaluate the agreement between self-reported data from a population-based cohort study with data from two large German health insurance companies. Methods Participants with available self-reported diagnoses of a history of stroke, atrial fibrillation (AF), heart failure (HF), and myocardial infarction (MI) from the baseline and the follow-up (after six years) surveys of the prospective population-based LIFE-Adult study were included in this study. Two health insurance companies provided ICD-10-GM codes. The agreement between the self-reports and health insurance data (HID) was examined by calculating sensitivity, specificity, Cohen`s Kappa, positive and negative predictive values. We used multivariable logistic regression models to examine whether odds ratios (OR) for the association between risk factors and the certain disease changed, depending on whether self-reports or HID was used as the dependent variable. Results One thousand seven hundred eighty four individuals with complete data were included in this interim analysis. Mean age was 58 (SD±12) years and 984 (55%) were female. 52 (2.9%) subjects reported a history of stroke, 99 (5.6%) AF, 63 (3.5%) HF, and 46 (2.6%) MI. Compared with the HID, a high specificity was found for all four diagnoses (stroke: 99% [95% CI 99.3-99.9]; AF: 99% [95% CI 98.1-99.2], HF: 98% [95% CI 97.6-98.9], and MI: 99% [95% CI 98.9-99.7]). Sensitivity ranged from 58% (95% CI 47.4-69.5) for stroke over 61% (95% CI 48.8-74.0) for MI, to 65% (95% CI 56.6-73.9) for AF. Sensitivity in HF was the lowest (20% [95% CI 14.4-26.5]). Conclusion The use of German health insurance data is a feasible method for verifying population-based self-reported diagnoses. The sensitivity varied among the self-reported diseases compared with the health insurance data, whereas the specificity was continuously high. The verification of self-reported diagnoses using health insurance data as an additional data source may be considered in future population-based assessments to reduce misclassification error of self-reported data.https://doi.org/10.1186/s13690-025-01606-3Population-basedHealth insuranceSelf-reportValidationAgreementHeart failure |
| spellingShingle | Samira Zeynalova Peter Worringen Stefan Bassler Anja Martin Katrin Czech Lars Greulich Matthias Reusche Ute Enders Nigar Reyes Maryam Yahiaoui-Doktor Matthias Collier Markus Loeffler Tina Stegmann A comparison between the self-report of chronic cardiovascular diseases with health insurance data: insights from the population-based LIFE-Adult study Archives of Public Health Population-based Health insurance Self-report Validation Agreement Heart failure |
| title | A comparison between the self-report of chronic cardiovascular diseases with health insurance data: insights from the population-based LIFE-Adult study |
| title_full | A comparison between the self-report of chronic cardiovascular diseases with health insurance data: insights from the population-based LIFE-Adult study |
| title_fullStr | A comparison between the self-report of chronic cardiovascular diseases with health insurance data: insights from the population-based LIFE-Adult study |
| title_full_unstemmed | A comparison between the self-report of chronic cardiovascular diseases with health insurance data: insights from the population-based LIFE-Adult study |
| title_short | A comparison between the self-report of chronic cardiovascular diseases with health insurance data: insights from the population-based LIFE-Adult study |
| title_sort | comparison between the self report of chronic cardiovascular diseases with health insurance data insights from the population based life adult study |
| topic | Population-based Health insurance Self-report Validation Agreement Heart failure |
| url | https://doi.org/10.1186/s13690-025-01606-3 |
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