Diabetes and Its Chronic Complications in the She Ethnic Minority Group of China
Bibliographic record
Abstract
OBJECTIVE: According to recent reports, the development of type 2 diabetes in China has soared at an alarming rate. However, most of the investigations were based on Han people, who account for the majority of people in China. Little is known about the prevalence of diabetes its chronic complications in the She people, who have their own traditional lifestyle and hereditable background, different from other Asian population. The present study investigated the prevalence of type 2 diabetes and associated risk factors in the adult population of She nationals. SUBJECTS AND METHODS: A total of 5,385 participants entered into the analysis eventually, including 2,308 men and 3,077 women. An oral glucose tolerance test was performed in subjects without diagnosed diabetes. Liver function, cardiovascular risk (brachial-ankle pulse wave velocity, estimated glomerular filtration rate, and abnormal Minnesota codes findings), uric acid, and neuropathy were tested to assess the profiles of associated risks. RESULTS: In general, the self-reported diabetes rate was 9.5%. After age and sex standardization, the prevalence of diabetes was 6.1% (6.7% for men and 5.7% for women) in She Chinese people. In logistic regression models, age, family history of diabetes, alcohol use, total cholesterol, and triglycerides were all significantly associated with the risk of diabetes in this cross-sectional study (all P<0.05). In all, 47.4% had cardiovascular risks, 19.4% had liver dysfunction, and 6.2% had hyperuricemia. For women, compared with the first quartile, log-transformed homeostasis model assessment for insulin resistance of the fourth quartile was significantly higher (P<0.05), and log-transformed homeostasis model assessment for β cells was also higher in the second, third, and fourth quartiles (all P<0.05). The prevalences of polyneuropathy in impaired fasting glucose (IFG), impaired glucose tolerance (IGT), IFG/IGT, and diabetes mellitus (DM) were 16.1%, 13.1%, 18.6%, and 28.4% separately, which was higher than that in normal glucose tolerance. The prevalences of polyneuropathy in IFG/IGT and DM were higher than that in IGT. CONCLUSIONS: The present study revealed that a total of 6.1% She people suffered from type 2 diabetes, which was lower than the average level of China, but the standardized prevalence of prediabetes was higher, 20.6%. Early peripheral neuropathy screening should be performed in the prediabetes population. The Toronto Clinical Neuropathy Scoring System is convenient to assess diabetic polyneuropathy in clinical practice and should be tested regularly for people in prediabetes. Liver dysfunction, headache, and insomnia, appearing before type 2 diabetes, should be assessed regularly to avoid deterioration.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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; 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".