| Title |
Predictive factors for cosmetic surgery: a hospital-based investigation
|
|---|---|
| Published in |
SpringerPlus, September 2016
|
| DOI | 10.1186/s40064-016-3188-z |
| Pubmed ID | |
| Authors |
Jun Li, Qian Li, Bei Zhou, Yanli Gao, Jiehua Ma, Jingyun Li |
| Abstract |
Cosmetic surgery is becoming increasingly popular in China. However, reports on the predictive factors for cosmetic surgery in Chinese individuals are scarce in the literature. We retrospectively analyzed 4550 cosmetic surgeries performed from January 2010 to December 2014 at a single center in China. Data collection included patient demographics and type of cosmetic surgery. Predictive factors were age, sex, marital status, occupational status, educational degree, and having had children. Predictive factors for the three major cosmetic surgeries were determined using a logistic regression analysis. Patients aged 19-34 years accounted for the most popular surgical procedures (76.9 %). The most commonly requested procedures were eye surgery, Botox injection, and nevus removal. Logistic regression analysis showed that higher education level (college, P = 0.01, OR 1.21) was predictive for eye surgery. Age (19-34 years, P = 0.00, OR 33.39; 35-50, P = 0.00, OR 31.34; ≥51, P = 0.00, OR 16.42), female sex (P = 0.00, OR 9.19), employment (service occupations, P = 0.00, OR 2.31; non-service occupations, P = 0.00, OR 1.76), and higher education level (college, P = 0.00, OR 1.39) were independent predictive factors for Botox injection. Married status (P = 0.00, OR 1.57), employment (non-service occupations, P = 0.00, OR 1.50), higher education level (masters, P = 0.00, OR 6.61), and having children (P = 0.00, OR 1.45) were independent predictive factors for nevus removal. The principal three cosmetic surgeries (eye surgery, Botox injection, and nevus removal) were associated with multiple variables. Patients employed in non-service occupations were more inclined to undergo Botox injection and nevus removal. Cohort study, Level III. |
X Demographics
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 36 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 36 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 7 | 19% |
| Student > Bachelor | 4 | 11% |
| Student > Master | 2 | 6% |
| Student > Postgraduate | 2 | 6% |
| Librarian | 1 | 3% |
| Other | 3 | 8% |
| Unknown | 17 | 47% |
| Readers by discipline | Count | As % |
|---|---|---|
| Psychology | 4 | 11% |
| Medicine and Dentistry | 4 | 11% |
| Nursing and Health Professions | 3 | 8% |
| Business, Management and Accounting | 2 | 6% |
| Agricultural and Biological Sciences | 2 | 6% |
| Other | 4 | 11% |
| Unknown | 17 | 47% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 19 September 2016.
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#19,553,478
of 24,051,764 outputs
Outputs from SpringerPlus
#1,280
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Outputs of similar age
#250,582
of 326,771 outputs
Outputs of similar age from SpringerPlus
#134
of 190 outputs
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