The role of multimorbidity and socio-economic characteristics as potential risk factors for Long Covid: evidence from the multilevel analysis of the Survey of Health, Ageing and Retirement in Europe’s corona surveys (2020–2021)
Bibliographic record
Abstract
BACKGROUND: A substantial proportion of individuals continue experiencing persistent symptoms following the acute stage of their Covid-19 illness. However, there is a shortage of population-based studies on Long Covid risk factors. OBJECTIVE: To estimate the prevalence of Long Covid in the population of middle-aged and older Europeans having contracted Covid-19 and to assess the role of multimorbidity and socio-economic characteristics as potential risk factors of Long Covid. METHODS: A population-based longitudinal prospective study involving a sample of respondents 50 years and older (n = 4,004) from 27 countries who participated in the 2020 and 2021 Survey of Health, Ageing and Retirement in Europe (SHARE), in particular the Corona Surveys. Analyses were conducted by a multilevel (random intercept) hurdle negative binomial model. RESULTS: Overall, 71.6% (95% confidence interval = 70.2-73.0%) of the individuals who contracted Covid-19 had at least one symptom of Long Covid up to 12 months after the infection, with an average of 3.06 (standard deviation = 1.88) symptoms. There were significant cross-country differences in the prevalence of Long Covid and number of symptoms. Higher education and being a man were associated with a lower risk of Long Covid, whilst being employed was associated with a higher risk of having Long Covid. Multimorbidity was associated with a higher number of symptoms and older age was associated with a lower number of symptoms. CONCLUSION: Our results provide evidence on the substantial burden of Long Covid in Europe. Individuals who contracted Covid-19 may require long-term support or further medical intervention, putting additional pressure on national health care systems.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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; a candidate call from one teacher head, not a consensus.
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".