| Title |
Analysis and determinants of Chinese navy personnel health status: a cross-sectional study
|
|---|---|
| Published in |
Health and Quality of Life Outcomes, July 2018
|
| DOI | 10.1186/s12955-018-0961-4 |
| Pubmed ID | |
| Authors |
Shali Xie, Hui Lin, Yi Meng, Jundong Zhu, Yanqi Zhang, Ling Zhang, Gaoming Li |
| Abstract |
There have been very few studies analyzing the relationship of physical and mental health status with health behaviors and deployment status in Chinese navy personnel. Thus, we undertook this survey to assess this relationship and identify specific factors affecting the physical and mental health status. The subjects enrolled in this study were selected from four units of the active-duty navy personnel in China, based on a cluster random sampling design. A total of 1200 Chinese navy personnel participated and completed the questionnaire survey that included veteran SF-36 form and a self-designed questionnaire regarding their sociodemographic characteristics, deployment status, self-rated health status and health behaviors. Totally 1200 questionnaires were distributed to different participants, while 1083 valid questionnaires were included in the final analysis. All data were analyzed using SPSS18.0 software. Based on the information provided by navy personnel, 17.82, 35.09 and 23.08% rated their health as excellent, very good and good, respectively. The mean score of physical component summary (PCS) and mental component summary (MCS) was 50.53 and 41.39, respectively. Length of service, binge drinking, regular drinking and BMI appeared to be associated with PCS score, while household income, binge drinking and BMI affected MCS score. Deployment status and smoking exhibited no significant association with PCS and MCS scores. Our study suggested that the sociodemographic factors like length of service and household income, along with behavioral risk factors like binge drinking, regular drinking and body mass index (BMI), seem to affect the physical and mental health status of Chinese navy personnel. However, additional data collection and more detailed analysis would still be required to develop a systematic, comprehensive and corresponding health education program to promote overall health status. |
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 34 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 34 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 6 | 18% |
| Lecturer | 3 | 9% |
| Student > Bachelor | 3 | 9% |
| Researcher | 3 | 9% |
| Student > Ph. D. Student | 2 | 6% |
| Other | 2 | 6% |
| Unknown | 15 | 44% |
| Readers by discipline | Count | As % |
|---|---|---|
| Psychology | 6 | 18% |
| Social Sciences | 4 | 12% |
| Medicine and Dentistry | 3 | 9% |
| Environmental Science | 1 | 3% |
| Agricultural and Biological Sciences | 1 | 3% |
| Other | 3 | 9% |
| Unknown | 16 | 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 12 July 2018.
All research outputs
#17,982,872
of 23,094,276 outputs
Outputs from Health and Quality of Life Outcomes
#1,519
of 2,189 outputs
Outputs of similar age
#236,065
of 326,767 outputs
Outputs of similar age from Health and Quality of Life Outcomes
#59
of 64 outputs
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