Background
Methods
Search strategy
Data extraction
Statistical analysis
Results
Characteristics of included studies
First Author | Study period | Sample size | Age (years) | Sex (% women) | Study location | Diagnostic criteria | Neurological tests | MCI prevalence (95%CI) |
---|---|---|---|---|---|---|---|---|
Chen ND | 2012 | 465 | ≥60 | 30.75% | Jiangsu | Petersen | 10.75% (8.25–13.9%) | |
Ding D | 2011 | 2985 | ≥60 | 54.22% | Shanghai | Petersen | 20.10% (18.73–21.61%) | |
Guo GY | 2013 | 940 | ≥60 | 56.81% | Hebei | Petersen | MoCA [77] | 14.47% (12.36–16.86%) |
Guo X | 2011 | 1367 | ≥60 | 50.40% | Hunan | DSM-IV | 10.17% (8.68–11.88%) | |
Hai S | 2007 | 202 | ≥80 | 25.74% | Sichuan | Petersen | 30.2% (24.28–36.85%) | |
He L | 2014 | 842 | ≥60 | 48.81% | Jiangxi | DSM-IV | 13.42% (11.28–15.89%) | |
Hu R | 2009 | 5887 | ≥55 | 56.38% | Mongolia | DSM-IV | 20.60% (19.59–21.66%) | |
Huang R | 2002 | 4697 | ≥60 | 58.85% | Guangzhou | Petersen | 5.47% (4.86–6.16%) | |
Jia J | 2009 | 10,276 | ≥65 | N/A | National | Petersen | 20.8% (20.02–21.59%) | |
Jiang LJ | 2016 | 895 | ≥60 | 51.06% | Jilin | NIA-AA | 5.36% (4.07–7.04%) | |
Lao ML | 2010 | 7665 | ≥55 | 54.22% | Hainan | Petersen | 4.25% (3.82–4.73%) | |
Li CP | 2014 | 1971 | ≥60 | 62.61% | Shandong | DSM-IV | 33.03% (30.99–35.14%) | |
Li W | 2019 | 3246 | ≥60 | N/A | Shanghai | Petersen | 17.07%* (15.79–18.42%) | |
Li X | 2013 | 1020 | ≥55 | 63.33% | Beijing | Petersen | 15.69% (13.58–18.05%) | |
Liao B | 2012 | 399 | ≥60 | 53.63% | Jiangxi | Petersen | 10.28% (7.67–13.64%) | |
Liu H | 2018 | 1796 | ≥60 | 53.95% | Shanghai | DSM-IV | 17.65% (15.96–19.48%) | |
Ma F | 2016 | 5067 | ≥65 | 57.80% | Tianjin | Petersen | 11.33% (10.48–12.23%) | |
Meng WQ | 2009 | 5452 | ≥55 | 53.62% | Inner Mongolia | Petersen | 22.50% (21.16–23.37%) | |
Pan ZD | 2012 | 300 | ≥60 | 57.14% | Shanghai | Petersen | 22.33% (17.99–27.38%) | |
Qin HY | 2012 | 4086 | ≥55 | 65.00% | Shanghai | Petersen | 14.98% (13.92–16.11%) | |
Qiu CJ | 2001 | 3910 | ≥55 | 50.82% | Chengdu | Petersen | 2.35% (1.92–2.88%) | |
Rao DP | 2009 | 2111 | ≥65 | 59.50% | Guangzhou | Petersen | 14.16% (12.74–15.72%) | |
Ren CF | 2011 | 946 | ≥60 | 49.26% | Jiangxi | DSM-IV | 10.47% (8.67–12.58%) | |
Song XZ | 2011 | 2279 | ≥60 | 51.21% | Guangzhou | Petersen | 7.33% (6.33–8.47%) | |
Sosa AL | 2007 | 2014 | ≥65 | 63.33% | National | DSM-IV | 7.99%* (6.89–9.26%) | |
Su C | 2011 | 341 | ≥60 | 52.49% | Guangzhou | Petersen | 12.32% (9.24–16.23%) | |
Sun Y | 2013 | 10,432 | ≥65 | 52.32% | Taiwan | NIA-AA | 19.64% (18.89–20.41%) | |
Tang MN | 1998 | 5385 | ≥55 | N/A | Chengdu | DSM-III | 1.21% (0.95–1.54%) | |
Tang Z | 2004 | 1865 | ≥60 | 51.90% | Beijing | Petersen | 11.64% (10.26–13.17%) | |
Wang T | 2012 | 1005 | ≥60 | N/A | Shanghai | DSM-IV | 22.29%* (19.82–24.96%) | |
Wang TT | 2017 | 1781 | ≥60 | 60.47% | Chongqing | Petersen | 11.73% (10.32–13.31%) | |
Wang YP | 2009 | 6152 | ≥65 | N/A | Shanxi | DSM-IV | 9.75% (9.04–10.52%) | |
Wang ZZ | 2013 | 689 | ≥55 | 62.70% | Ningxia | Chinese Dementia guideline | 18.29% (15.58–21.35%) | |
Wu Y | 2014 | 1846 | ≥60 | 53.36% | Jiangsu | Petersen | 17.17% (15.52–18.96%) | |
Xiao SF | 2016 | 1068 | ≥60 | N/A | Shanghai | Petersen | WHO-BCAI [82] | 25.00% (22.50–27.68%) |
Xu SJ | 2011 | 2426 | ≥60 | 60.68% | Hebei | Petersen | 21.68% (20.09–23.37%) | |
Yin LY | 2009 | 1011 | ≥65 | 59.45% | Hebei | Petersen | 6.63% (5.25–8.33%) | |
Yuan J | 2010 | 3311 | ≥60 | 66.89% | Shanghai | Petersen | 19.06% (17.76–20.43%) | |
Zhang XQ | 2012 | 1764 | ≥60 | 55.95% | Changsha | Petersen | 16.27% (14.62–18.07%) | |
Zhou DS | 2010 | 1227 | ≥60 | 56.32% | Zhejiang | DSM-IV | 8.72% (7.27–10.43%) | |
Zhu XQ | 2008 | 1511 | ≥60 | 54.60% | Xinjiang | DSM-IV | 9.79% (8.40–11.40%) |
Publication bias
No. | Study | External validity | Internal validity | Overall |
---|---|---|---|---|
1 | Chen ND, 2012 | Moderate Risk | Moderate Risk | Moderate Risk |
2 | Ding D, 2015 | Low Risk | Low Risk | Low Risk |
3 | Guo GY, 2013 | Moderate Risk | Moderate Risk | Moderate Risk |
4 | Guo XY, 2013 | Moderate Risk | Moderate Risk | Moderate Risk |
5 | Hai S, 2011 | Moderate Risk | Moderate Risk | Moderate Risk |
6 | He L, 2015 | Low Risk | Moderate Risk | Moderate Risk |
7 | Hu R, 2012 | Moderate Risk | Moderate Risk | Moderate Risk |
8 | Huang R, 2008 | Low Risk | Low Risk | Low Risk |
9 | JIA J, 2013 | Low Risk | Low Risk | Low Risk |
10 | Jiang LJ, 2017 | Moderate Risk | Moderate Risk | Moderate Risk |
11 | Lao ML, 2011 | Moderate Risk | Moderate Risk | Moderate Risk |
12 | Li CP, 2014 | low Risk | Moderate Risk | Moderate Risk |
13 | Li X, 2013 | Moderate Risk | Moderate Risk | Moderate Risk |
14 | Li W, 2020 | low Risk | Low Risk | Low Risk |
15 | Liao B, 2012 | Moderate Risk | Moderate Risk | Moderate Risk |
16 | Liu H, 2018 | low Risk | Moderate Risk | Moderate Risk |
17 | Ma F, 2016 | Low Risk | Low Risk | Low Risk |
18 | Meng WQ, 2010 | Moderate Risk | Moderate Risk | Moderate Risk |
19 | Pan HY, 2012 | Moderate Risk | High Risk | High Risk |
20 | Pan ZD, 2012 | Low Risk | Moderate Risk | Moderate Risk |
21 | Peng Z, 2019 | Moderate Risk | High Risk | High Risk |
22 | Qin HY, 2014 | Low Risk | Low Risk | Low Risk |
23 | Qiu CJ, 2003 | Moderate Risk | Low Risk | Moderate Risk |
24 | Rao D, 2018 | Low Risk | Low Risk | Low Risk |
25 | Ren CF, 2013 | Moderate Risk | Low Risk | Moderate Risk |
26 | Song XZ, 2012 | Low Risk | Moderate Risk | Moderate Risk |
27 | Sosa AL, 2012 | Moderate Risk | Moderate Risk | Moderate Risk |
28 | Su C, 2013 | Moderate Risk | Moderate Risk | Moderate Risk |
29 | Sun Y, 2014 | Low Risk | Moderate Risk | Moderate Risk |
30 | Tang Z, 2007 | Low Risk | Moderate Risk | Moderate Risk |
31 | Tang MN, 2000 | Low Risk | Moderate Risk | Moderate Risk |
32 | Wang T, 2017 | Low Risk | Moderate Risk | Moderate Risk |
33 | Wang TT, 2017 | Low Risk | Low Risk | Low Risk |
34 | Wang YP, 2011 | Moderate Risk | Moderate Risk | Moderate Risk |
35 | Wang ZZ, 2013 | Moderate Risk | Moderate Risk | Moderate Risk |
36 | Wu L, 2016 | Moderate Risk | High Risk | High Risk |
37 | Wu Y, 2017 | Low Risk | Moderate Risk | Moderate Risk |
38 | Xiao SF, 2016 | Low Risk | Low Risk | Low Risk |
39 | Xu SJ, 2014 | Low Risk | Moderate Risk | Moderate Risk |
40 | Yin LY, 2010 | Low Risk | Moderate Risk | Moderate Risk |
41 | Yuan J, 2013 | Moderate Risk | Moderate Risk | Moderate Risk |
42 | Zhang XQ, 2014 | Low Risk | Low Risk | Low Risk |
43 | Zhong SY, 2018 | Moderate Risk | High Risk | High Risk |
44 | Zhou DS, 2011 | Moderate Risk | Low Risk | Moderate Risk |
45 | Zhu XQ, 2009 | Moderate Risk | Low Risk | Moderate Risk |
Robust tests for pooled results
lnhr | Coef. | Std. Err. | t | P > |t| | [95% Conf. Interval] | |
---|---|---|---|---|---|---|
Age | .2187126 | .1562825 | 1.40 | 0.171 | −.0988917 | .5363169 |
Study period | .3282157 | .1214176 | 2.70 | 0.011 | .0814654 | .574966 |
Diagnostic criteria | −.1795994 | .1203679 | −1.49 | 0.145 | −.4242164 | .0650176 |
Constant | −3.146882 | .5048756 | −6.23 | 0.000 | −4.172913 | −2.120851 |
Prevalence of MCI and aMCI – results of meta-analyses
Results of subgroup analyses
Subgroup | Included studies | Study participants (sample size) | Random-effect Model | Heterogeneity | ||
---|---|---|---|---|---|---|
MCI Prevalence (95% CI) | p | I2 | Ph | |||
Age (Years) | ||||||
55–59 | 3 | 5951 | 0.076(0.025–0.226) | < 0.001 | 99.2% | 0.922 |
60–69 | 24 | 23,095 | 0.095(0.074–0.121) | < 0.001 | 97.8% | 0.356 |
70–79 | 25 | 22,902 | 0.146 (0.124–0.171) | < 0.001 | 96.6% | 0.153 |
≥ 80 | 25 | 9397 | 0.236 (0.204–0.274) | < 0.001 | 93.5% | 0.122 |
Sex | ||||||
Men | 34 | 45,609 | 0.115 (0.097–0.136) | < 0.001 | 97.4% | 0.233 |
Women | 34 | 36,027 | 0.138 (0.117–0.163) | < 0.001 | 98.3% | 0.224 |
Residency | ||||||
Urban | 32 | 71,801 | 0.114 (0.098–0.132) | < 0.001 | 98.4% | 0.174 |
Rural | 12 | 25,137 | 0.136 (0.106–0.176) | < 0.001 | 98.8% | 0.193 |
Living status | ||||||
With family | 10 | 13,941 | 0.141 (0.110–0.182) | < 0.001 | 97.6% | 0.157 |
alone | 10 | 3518 | 0.182 (0.136–0.244) | < 0.001 | 95.0% | 0.206 |
Education attainment | ||||||
< Primary school | 18 | 10,974 | 0.172 (0.122–0.243) | < 0.001 | 98.3% | 0.540 |
Primary school | 18 | 14,502 | 0.120 (0.083–0.174) | < 0.001 | 98.5% | 0.623 |
Middle school | 21 | 11,367 | 0.091 (0.072–0.115) | < 0.001 | 94.3% | 0.418 |
≥ High school | 21 | 9568 | 0.063 (0.046–0.085) | < 0.001 | 94.2% | 0.515 |
Diagnostic criteria | ||||||
Peterson | 25 | 67,267 | 0.129 (0.107–0.154) | < 0.001 | 98.9% | 0.209 |
DSM-IV | 9 | 21,699 | 0.135 (0.097–0.188) | < 0.001 | 99.0% | 0.257 |
NIA-AA | 2 | 11,327 | 0.103 (0.029–0.369) | < 0.001 | 98.8% | 0.833 |
Study period | ||||||
< 2005 | 4 | 15,857 | 0.037 (0.016–0.087) | < 0.001 | 99.2% | 0.769 |
≥ 2005 | 30 | 90,510 | 0.141 (0.124–0.160) | < 0.001 | 98.6% | 0.142 |