| Literature DB >> 26649171 |
Kit Yee Chan1, Fei-Fei Zhao2, Shijiao Meng2, Alessandro R Demaio3, Craig Reed4, Evropi Theodoratou4, Harry Campbell4, Wei Wang5, Igor Rudan6.
Abstract
BACKGROUND: Dramatic development and changes in lifestyle in many low and middle-income countries (LMIC) over the past three decades may have affected mental health of their populations. Being the largest country and having the most striking record of development, industrialization and urbanization, China provides an important opportunity for studying the nature and magnitude of possible effects.Entities:
Mesh:
Year: 2015 PMID: 26649171 PMCID: PMC4663755 DOI: 10.7189/jogh.05.010410
Source DB: PubMed Journal: J Glob Health ISSN: 2047-2978 Impact factor: 4.413
Figure 1PRISMA diagram of the study selection. †The large majority was excluded because they were duplicate returns of the same reference under different search terms or in different databases; the others were excluded because they were irrelevant to the topic of our study, provided no numerical estimates, or studied Chinese populations outside of mainland China. *Reports of the same results in different journals.
Characteristics of the cross–sectional studies
| Study characteristics | Number of studies (n = 42) |
|---|---|
| <5000 | 8 (19.0%) |
| 5001–10 000 | 9 (21.4%) |
| 10 001–20 000 | 11 (26.2%) |
| 20 001–60 000 | 7 (16.7%) |
| >60 000 | 7 (16.7%) |
| 1990–1994 | 6 (14.3%) |
| 1995–1999 | 6 (14.3%) |
| 2000–2004 | 15 (35.7%) |
| 2005–2010 | 13 (31.0%) |
| 2011 | 2 (4.8%) |
| Urban | 4 (9.5%) |
| Rural | 10 (23.8%) |
| Both | 28 (66.7%) |
| Chinese Classification of Mental Disorders (CCMD)–II: | 9 (21.4%) |
| CCMD–II–R | 11 (26.2%) |
| CCMD–III | 8 (19.1%) |
| DSM–III–R | 4 (9.5%) |
| DSM–IV | 4 (9.5%) |
| ICD–9 | 2 (4.8%) |
| ICD–10 | 10 (23.8%) |
DSM – Diagnostic and Statistical Manual of Mental Disorders, ICD – International Classification of Diseases
*Proportions do not add up to 100% because several studies used both CCMD and DSM/ICD case definition.
Figure 2Geographic location of 48 study sites in 42 retained studies. The studies are shown on the map of China that represents the areas of urban and rural areas (I = most developed; IV = least developed) around the mid–point of the study period.
Estimates of lifetime and point prevalence of schizophrenia in urban and rural settings in China for the year 1990, 2000 and 2010 (with 95% credible intervals)*
| Outcome/Setting | Year | ||
|---|---|---|---|
| Urban | 0.32% (0.29–0.36%) | 0.47% (0.44–0.50%) | 0.68% (0.57–0.81%) |
| Rural | 0.37%(0.33–0.42%) | 0.36% (0.35–0.38%) | 0.35% (0.33–0.38%) |
| Urban | 0.39% (0.37–0.41%) | 0.57% (0.55–0.59%) | 0.83% (0.75–0.91%) |
| Rural | 0.37% (0.34–0.40%) | 0.43% (0.42–0.44%) | 0.50% (0.47–0.53%) |
| Urban | 849 (805–892) | 1935 (1867–2003) | 4412 (3987–4837) |
| Rural | 2245 (2063–2427) | 2607 (2546–2667) | 2744 (2580–2901) |
| All China | 3094 (2868–3319) | 4542 (4413–4670) | 7156 (6566–7748) |
*The estimates are based on Bayesian methods and represent the median of posterior distribution of probability of having schizophrenia in the year 1990, 2000 and 2010. Computation of the number of cases is based on estimates of lifetime prevalence.
Figure 3Absolute number of schizophrenia cases in China 1990–2010 by type of residency, based on estimates of lifetime prevalence.