Hyperhidrosis Prevalence and Demographical Characteristics in Dermatology Outpatients in Shanghai and Vancouver
Bibliographic record
Abstract
BACKGROUND: There is a wide variation in the reported prevalence of primary hyperhidrosis in the literature. Further, it is unknown if primary hyperhidrosis is a lifelong condition, or if demographical factors influence hyperhidrosis prevalence. OBJECTIVES: This study aims to examine the prevalence of hyperhidrosis in multiple ethnic groups from two ethnically diverse cities and to determine if the prevalence of primary hyperhidrosis changes according to age, gender, ethnicity, body mass index, and geographical locations. METHODS: In total, 1010 consecutive subjects attending dermatology outpatient clinics in Shanghai Skin Disease Hospital and 1018 subjects in Skin Care Center of Vancouver General Hospital were invited to fill out a questionnaire on their presenting concerns, demographical information, and sweating symptoms. The subjects were then classified to have primary hyperhidrosis using the criteria of International Hyperhidrosis Society, late-onset hyperhidrosis, or no-hyperhidrosis. The prevalence of primary HH and late-onset HH was calculated for the entire study population and in subgroups stratified according to age of examination, sex, ethnicity, presenting diagnosis, body mass index, and specific study cities. Multivariate logistic regression analyses were performed to assess the impact of these factors on HH prevalence. RESULTS: The prevalence of primary hyperhidrosis is very similar in Shanghai and in Vancouver, at 14.5% and 12.3% respectively. In addition, 4.0% of subjects in Shanghai and 4.4% subjects in Vancouver suffer from late-onset HH. Primary HH has highest prevalence in those younger than 30 years of age, decreasing dramatically in later years. Caucasian subjects are at least 2.5 times more likely to develop axillary hyperhidrosis compared to Chinese subjects. Obesity does not have much influence on primary HH presentation, although it does increase significantly the development of late-onset HH. Finally, there is no major difference of hyperhidrosis between Chinese subjects in Shanghai and Vancouver. LIMITATIONS: The data were gathered according to patients' self-reports only and the sample size was relatively small in some groups after stratification for gender, ethnicity and age. CONCLUSION: Prevalence of primary HH and late-onset HH is similar in dermatology outpatients independent of geographical locations. However, certain specific HH subtypes can show great variations according to ethnicity, age, body mass index and sex.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".