| Title |
Prevalence of osteoporosis in China: a meta-analysis and systematic review
|
|---|---|
| Published in |
BMC Public Health, October 2016
|
| DOI | 10.1186/s12889-016-3712-7 |
| Pubmed ID | |
| Authors |
Peng Chen, Zhanzhan Li, Yihe Hu |
| Abstract |
We conducted a systematic review and meta-analysis to obtain a reliable estimation of the prevalence of osteoporosis in China and to characterize its epidemiology. We identified relevant studies via a search of literature published from 2003 to October 2015 in the PubMed, Web of Science, China National Knowledge Infrastructure, Wanfang and Weipu databases. Both Chinese and WHO criteria were considered acceptable for the diagnosis of osteoporosis. Prevalence estimates were obtained using random effects models. Meta-regression analysis was used to explore the sources of heterogeneity, and publication bias was evaluated by visually inspecting funnel plots. Overall, 69 articles were included in this study. An obvious increase in the prevalence of osteoporosis was identified over the past 12 years (prevalence of 14.94 % before 2008 and 27.96 % during the period spanning 2012-2015). The prevalence of osteoporosis was higher in females than in males (25.41 % vs. 15.33 %) and increased with age. Osteoporosis prevalence was higher in rural than in urban areas (20.87 % vs. 23.92 %) and higher in southern than in northern areas (23.17 % vs. 20.13 %). At present, the pooled prevalence of osteoporosis in people aged 50 years and older was more than twice the pooled prevalence identified in 2006 (34.65 % vs. 15.7 %). The application of different diagnostic criteria could have an impact on prevalence estimation (19.7 % vs. 29.3 %). Meta-regression suggested that study setting also influenced the estimation of point prevalence (P = 0.022). The prevalence of osteoporosis in China has increased over the past 12 years, affecting more than one-third of people aged 50 years and older. The prevalence of osteoporosis increased with age and was higher in females than in males. Prevention and control measures have become all the more important given the increase in osteoporosis prevalence, and three-step prevention programmes should be implemented. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Australia | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 135 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 135 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 20 | 15% |
| Student > Bachelor | 15 | 11% |
| Researcher | 11 | 8% |
| Student > Ph. D. Student | 10 | 7% |
| Student > Postgraduate | 9 | 7% |
| Other | 20 | 15% |
| Unknown | 50 | 37% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 37 | 27% |
| Nursing and Health Professions | 10 | 7% |
| Biochemistry, Genetics and Molecular Biology | 6 | 4% |
| Social Sciences | 6 | 4% |
| Economics, Econometrics and Finance | 4 | 3% |
| Other | 20 | 15% |
| Unknown | 52 | 39% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 26 February 2020.
All research outputs
#14,273,624
of 22,890,496 outputs
Outputs from BMC Public Health
#10,378
of 14,926 outputs
Outputs of similar age
#183,159
of 321,456 outputs
Outputs of similar age from BMC Public Health
#192
of 273 outputs
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