Burden of Diabetes on the Ability to Work
Bibliographic record
Abstract
Type 2 diabetes is an increasingly common disease (1) that places a considerable economic burden on society. An estimated 171 million people were suffering from diabetes in 2000, and this number could total 366 million by 2030 (1). Type 2 diabetes accounts for more than 90% of all diabetes cases, and it often appears in middle age (2). In 2010, the prevalence of diabetes in the U.S. was 11.3 and 26.9% among individuals aged 20 years or over and 65 years or older (2), respectively. In 2007, costs related to diabetes in the U.S. were an estimated $174 billion; $116 billion in direct costs and $58 billion in indirect costs (3). Direct costs include the cost of personal expenditures, drugs, and health care services, whereas indirect costs include lost productivity at work. Lost productivity at work may be measured through absenteeism (time lost from work due to illness), presenteeism (time at work impaired due to illness), productivity (time lost from work due to illness plus time at work impaired due to illness), or early retirement (retirement before the official retirement age due to illness). Lost productivity at work is an important concern for employees, employers, and society. Moreover, the complications related to diabetes are a major cause of disability, reduced quality of life, and death (4). Employees with diabetes may stop working prematurely (5–8) and may experience unemployment (7,9–12), which could translate into a reduction in earned income and savings (13) and loss of self-esteem (14). For employers too, lost productivity due to absenteeism (6,8,13,15–23), presenteeism (17), and early retirement (5–7) is an important economic issue. To the best of our knowledge, there are no published systematic reviews answering the following question: Do individuals …
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.027 | 0.004 |
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 source (direct Gemma or distilled Codex), 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".