Does Pre‐existing Diabetes Correlate with Long COVID‐19 in Europe? Evidence from the Analysis of the Survey of Health, Ageing and Retirement in Europe’s Corona Surveys
Bibliographic record
Abstract
Background: A substantial proportion of those infected with COVID-19 are presenting with persistent symptoms, referred to as long COVID-19. Emerging evidence suggests that the presence of pre-existing chronic conditions, such as diabetes, may increase the risk of long COVID-19. Objectives: To investigate whether having pre-existing diabetes increases the risk of developing long COVID-19 in the population of middle-aged and older adults (≥50 years old) in Europe, while assessing if this relationship can be accounted for or is modified by the known long COVID-19 and diabetes risk factors (age, sex, hospitalization, pre-existing hypertension, and weight status). Methods: = 4,004) with probable or confirmed COVID-19 infection from 27 countries that participated in both waves 7 and 8 of the Survey of Health, Ageing and Retirement in Europe and its 2020 and 2021 Corona Surveys. Logistic regression modeling was performed. Results: Overall, 66.8% of the respondents affected by COVID-19 infection reported at least one long COVID-19 symptom; 55.2% were female, and the average age was 64.6 years; 13.2% had pre-existing diabetes. Respondents with pre-existing diabetes had significantly higher odds of developing long COVID-19, compared to those without diabetes (OR = 1.37; 95% CI = 1.12, 1.68). This relationship remained significant (OR = 2.00; 98% CI = 0.25, 1.14) after adjusting for sex (OR = 1.64 for females; 95% CI = 1.43, 1.88), hospitalization for COVID-19 illness (OR = 3.19; 95% CI = 2.41, 4.23), pre-existing hypertension (OR = 1.17; 95% CI = 1.01, 1.36), and overweight (OR = 1.31; 95% CI = 1.11, 1.56) and obese (OR = 1.77; 95% CI = 1.44, 2.19) weight status. The effect of pre-existing diabetes on the risk of long COVID-19 is moderated by age; it was highest at the age of 50 (OR = 2.00; 95% CI = 1.28, 3.14), and then, it declined with age. Conclusions: There is a relationship between pre-existing diabetes and long COVID-19, even after controlling for literature-based confounding factors, with age having a moderating effect on this relationship.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.043 | 0.041 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".