Geographic Distribution and Temporal Trends of HIV-1 Subtypes through Heterosexual Transmission in China: A Systematic Review and Meta-Analysis
Abstract
:1. Introduction
2. Methods
2.1. Literature Search Strategy
2.2. Inclusion and Exclusion Criteria
2.3. Data Extraction
2.4. Statistical Analysis
3. Results
3.1. Study Identification and Selection
3.2. General Characteristic of the Included Studies
3.3. The Overall Proportion of HIV-1 Subtypes
3.4. Temporal Trend of HIV-1 Subtypes
3.5. Geographic Distribution of HIV-1 Subtypes
3.6. Amplification of HIV-1 Gene Region
3.7. Sensitivity Analysis
4. Discussion
5. Conclusions
Supplementary Materials
Acknowledgments
Author Contributions
Conflicts of Interest
References
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First Author, Publication Year [Reference] | Study Period (Mid-Year) * | Location | Gene Amplification Region | Sample Sizes | The Frequency and Proportion of Different HIV-1 Subtypes | |||||
---|---|---|---|---|---|---|---|---|---|---|
CRF01_AE | CRF07_BC | CRF08_BC | B/B‘ | C | Other Subtypes | |||||
Ye, J.R., 2009 [24] | 2007 | Beijing | gag | 36 | 9 (25.00%) | 14 (38.89%) | 2 (5.56%) | 10 (27.78%) | - | 1 (2.78%) |
He, H.L., 2012 [25] | 2009 | Guangdong | env, pol | 104 | 68 (65.38%) | 16 (15.38%) | 4 (3.85%) | 6 (5.77%) | - | 10 (9.62%) |
Wu, X.F., 2015 [26] | 2013 | Zhejiang | gag | 78 | 18 (23.08%) | 39 (50.00%) | 12 (15.38%) | 9 (11.54%) | - | - |
Fan, W., 2015 [27] | 2006–2014 (2010) | Jiangsu | env, gag | 103 | 54 (52.43%) | 21 (20.39%) | 12 (11.65%) | 14 (13.59%) | - | 2 (1.94%) |
Yan, Q.L., 2016 [28] | 2014 | Jiangsu | env | 136 | 73 (53.68%) | 25 (18.38%) | 12 (8.82%) | 20 (14.71%) | - | 6 (4.41%) |
Yang, H.T., 2009 [29] | 2006 | Jiangsu | env, gag | 43 | 9 (20.93%) | 14 (32.56%) | 5 (11.63%) | 10 (23.26%) | 5 (11.63%) | - |
Li, X.J., 2009 [30] | 1994–2002 (1998) | Yunnan | pol, gag | 15 | 1 (6.67%) | 4 (26.67%) | 6 (40.00%) | 4 (26.67%) | - | - |
Wu, J., 2016 [31] | 2007–2013 (2010) | Shanghai | pol | 420 | 233 (55.48%) | 89 (21.19%) | 28 (6.67%) | 45 (10.71%) | 8 (1.90%) | 17 (4.05%) |
Tao, J., 2016 [32] | 2013 | Shanghai | pol | 289 | 157 (54.33%) | 83 (28.72%) | 10 (3.46%) | 21 (7.27%) | 1 (0.35%) | 17 (5.88%) |
Zhang, X.C., 2015 [33] | 2013 | Shanghai | pol | 31 | 18 (58.06%) | 8 (25.81%) | 2 (6.45%) | 2 (6.45%) | 1 (32.26%) | - |
Zhao, G.L., 2012 [34] | 1992–2008 (2000) | Guangdong | env | 198 | 137 (69.19%) | 14 (7.07%) | 8 (4.04%) | 34 (17.17%) | 2 (1.01%) | 3 (1.52%) |
Kong, D.F., 2105 [35] | 2007–2010 (2008–2009) | Guangdong | env, gag | 199 | 118 (59.30%) | 41 (20.60%) | 15 (7.54%) | 17 (8.54%) | 7 (3.52%) | 1 (0.50%) |
Shi, X.D., 2012 [36] | 2010 | Guangdong | env, gag | 57 | 37 (64.91%) | 7 (12.28%) | 6 (10.53%) | 6 (10.53%) | 1 (1.75%) | - |
Wang, X., 2012 [37] | 2010 | Tianjin | gag | 30 | 23 (76.67%) | 1 (3.33%) | - | 6 (20.00%) | - | - |
Zhao, C.Y., 2011 [38] | 2009 | Hebei | env, gag | 60 | 18 (30.00%) | 9 (15.00%) | 4 (6.67%) | 26 (43.33%) | 1 (1.67%) | 2 (3.33%) |
Li, J.J., 2016 [39] | 2012–2014 (2013) | Yunnan | env | 167 | 32 (19.16%) | 100 (59.88%) | 15 (8.98%) | 6 (35.93%) | 3 (1.80%) | 11 (6.59%) |
Chen, M., 2012 [40] | 2011 | Yunnan | env, gag | 172 | 43 (25.00%) | 3 (1.74%) | 8 (4.65%) | 5 (2.91%) | 70 (40.70%) | 43 (25.00%) |
Wang, H., 2016 [41] | 2010–2012 (2011) | Guangxi | pol | 86 | 58 (67.44%) | 18 (20.93%) | 7 (8.14%) | 2 (2.33%) | - | 1 (1.16%) |
Zheng, M., 2015 [42] | 2013 | Shanghai | pol | 184 | 98 (53.26%) | 59 (32.07%) | 13 (7.07%) | 12 (6.52%) | - | 2 (1.08%) |
Wu, J., 2012 [43] | 2010 | Shanghai | pol | 14 | 10 (71.43%) | 3 (21.43%) | - | - | 1 (7.14%) | - |
Bao, Y., 2010 [44] | 2009 | Guangdong | env, gag | 123 | 76 (61.79%) | 35 (28.46%) | 5 (4.07%) | 5 (4.07%) | 2 (1.63%) | - |
Bao, Y., 2012 [45] | 2010 | Guangdong | env, gag | 142 | 81 (57.04%) | 34 (23.94%) | 9 (6.34%) | 11 (7.75%) | 6 (4.23%) | 1 (0.70%) |
Pan, X.H., 2007 [46] | 2003–2005 (2004) | Zhejiang | gag | 59 | 23 (38.98%) | 18 (30.51%) | 7 (11.86%) | 10 (16.95%) | - | 1 (1.69%) |
Qiu, D.H., 2013 [47] | 2011 | Zhejiang | pol | 87 | 45 (51.72%) | 16 (18.39%) | 18 (20.69%) | 7 (8.05%) | 1 (1.15%) | - |
Ye, J.R., 2013 [48] | 2006–2010 (2008) | Beijing | gag | 62 | 13 (20.97%) | 9 (14.52%) | 4 (6.45%) | 19 (30.65%) | 7 (11.29%) | 10 (16.13%) |
Jin, M.H., 2014 [49] | 2008–2012 (2010) | Zhejiang | gag | 30 | 6 (20.00%) | 17 (56.67%) | 3 (10.00%) | 4 (13.33%) | - | - |
Zhang, S., 2010 [50] | 2009 | Zhejiang | pol | 21 | 7 (33.33%) | 5 (23.81%) | 2 (9.52%) | 3 (14.29%) | 4 (19.05%) | - |
Shen, P., 2015 [51] | 2014 | Guangxi | gag | 62 | 47 (75.81%) | 6 (9.68%) | 8 (12.90%) | - | - | 1 (1.61%) |
Cheng, H., 2015 [52] | 2012–2013 (2012–2013) | Jiangsu | env | 87 | 38 (43.68%) | 19 (21.84%) | 14 (16.09%) | - | 2 (2.30%) | 14 (16.10%) |
Han, X.X., 2010 [53] | 2000–2008 (2004) | Liaoning | gag | 70 | 26 (37.14%) | 5 (7.14%) | 3 (4.29%) | 26 (37.14%) | 1 (1.43%) | 9 (12.86%) |
Chen, S., 2012 [54] | 2009 | Guangdong | pol, env | 85 | 56 (65.88%) | 14 (16.47%) | 4 (4.71%) | 6 (7.06%) | - | 5 (5.88%) |
Bao, L.L., 2008 [55] | 1996–2005 (2000–2001) | Yunnan | Pol, env | 44 | 27 (61.36%) | - | 15 (34.09%) | - | - | 2 (4.54%) |
Li, L., 2013 [56] | 2009 | Guangxi | gag, pol | 236 | 189 (80.08%) | 15 (6.36%) | 24 (10.17%) | 4 (1.69%) | - | 4 (1.69%) |
Deng, Y.Y., 2014 [57] | 2011–2012 (2011–2012) | Fujian | env, gag, pol | 61 | 28 (45.90%) | 21 (34.43%) | 6 (9.84%) | 4 (6.56%) | - | 2 (3.28%) |
Yang, S.M., 2012 [58] | 2008–2009 (2008–2009) | Yunnan | env, gag, pol | 402 | 117 (29.10%) | 27 (6.72%) | 212 (52.74%) | 7 (1.74%) | 7 (1.74%) | 32 (7.96%) |
Zhang, J.F., 2013 [59] | 2009 | Zhejiang | gag | 146 | 87 (59.59%) | 22 (15.07%) | 15 (10.27%) | 20 (13.70%) | 1 (0.68%) | 1 (0.68%) |
Pan, H.X., 2010 [60] | 2008 | Zhejiang | gag | 66 | 26 (39.39%) | 4 (6.06%) | 14 (21.21%) | 16 (24.24%) | 4 (6.06%) | 2 (3.03%) |
Chen, Y.Y., 2014 [61] | 2009–2011 (2010) | Yunnan | pol | 238 | 94 (39.50%) | 32 (13.44%) | 88 (36.97%) | 3 (12.61%) | - | 21 (8.82%) |
Li, Y., 2011 [62] | 2007–2008 (2007–2008) | Hubei | gag | 31 | 2 (6.45%) | 1 (3.23%) | - | 28 (90.32%) | - | - |
Qin, C.H., 2016 [63] | 2011–2013 (2012) | Jiangsu | env, pol | 17 | 10 (58.82%) | 4 (23.53%) | 1 (5.88%) | - | - | 2 (11.76%) |
Gui, T., 2016 [64] | 2012 | Hebei | gag, pol | 33 | 10 (30.30%) | 2 (6.06%) | 1 (3.03%) | 14 (42.42%) | 4 (12.12%) | 2 (6.06%) |
Zhong, P., 2003 [65] | 1999–2001 (2000) | Shanghai | env, gag | 16 | 6 (37.50%) | - | 1 (6.25%) | 4 (25.00%) | 2 (12.50%) | 3 (18.75%) |
Subgroups | CRF01_AE | CRF07_BC | CRF08_BC | |||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
N | Proportion, % (95% CI) | p #, I2 | p * | N | Proportion, % (95% CI) | p #, I2 | p * | N | Proportion, % (95% CI) | p #, I2 | p * | |
Study region | <0.01 | <0.01 | <0.01 | |||||||||
East provinces | 18 | 46.05 (40.44–51.70) | <0.01, 79.9% | 17 | 24.93 (20.06–30.11) | <0.01, 80.1% | 17 | 10.10 (7.44–13.08) | <0.01, 66.8% | |||
South provinces | 8 | 61.75 (57.18–66.21) | 0.04, 50.5% | 8 | 18.97 (12.95–25.80) | <0.01, 84.2% | 8 | 5.64 (4.21–7.24) | 0.39, 4.3% | |||
North provinces | 6 | 35.73 (22.50–50.12) | <0.01, 83.4% | 6 | 12.67 (5.58–21.85) | <0.01, 75.5% | 5 | 5.22 (2.64–8.48) | 0.95, 0.0% | |||
Southwest provinces | 9 | 44.80 (28.17–62.03) | <0.01, 97.5% | 8 | 15.19 (5.13–29.02) | <0.01, 97.2% | 9 | 20.53 (8.51–35.87) | <0.01, 97.4% | |||
Time period | <0.01 | <0.01 | 0.24 | |||||||||
–2006 | 7 | 39.18 (22.58–57.09) | <0.01, 91.5% | 5 | 18.25 (7.16–32.65) | <0.01, 88.0% | 7 | 12.77 (4.92–23.17) | <0.01, 84.4% | |||
2007–2009 | 13 | 44.48 (32.00–57.31) | <0.01, 95.9% | 13 | 14.64 (9.98–19.98) | <0.01, 85.3% | 12 | 10.43 (3.03–21.16) | <0.01, 96.8% | |||
2010–2012 | 13 | 50.23 (41.35–59.10) | <0.01, 89.0% | 13 | 17.45 (11.09–24.81) | <0.01, 89.1% | 11 | 10.34 (4.71–17.63) | <0.01, 92.1% | |||
2013–2014 | 9 | 47.55 (36.16–59.07) | <0.01, 93.1% | 9 | 28.96 (19.37–39.75) | <0.01, 92.7% | 9 | 9.32 (6.29–12.82) | <0.01, 68.6% | |||
Amplified gene region | 0.08 | <0.01 | 0.55 | |||||||||
Only one | 24 | 45.16 (38.14–52.28) | <0.01, 91.2% | 24 | 21.14 (15.58–27.26) | <0.01, 91.8% | 21 | 10.39 (6.94–14.40) | <0.01, 88.2% | |||
Two or more | 18 | 47.78 (37.70–57.96) | <0.01, 94.5% | 16 | 16.23 (10.97–22.24) | <0.01, 89.5% | 18 | 10.95 (4.63-19.25) | <0.01, 95.7% | |||
Subgroups | B/B’ | C | ||||||||||
N | Proportion, % (95% CI) | p # , I2 | p * | N | Proportion, % (95% CI) | p # , I2 | p * | |||||
Study region | <0.01 | <0.01 | ||||||||||
East provinces | 15 | 12.09 (9.47–14.96) | <0.01, 57.2% | 11 | 2.83 (0.86–5.59) | <0.01, 71.4% | ||||||
South provinces | 8 | 8.28 (5.50–11.52) | <0.01, 62.7% | 5 | 2.28 (1.23–3.58) | 0.32, 13.7% | ||||||
North provinces | 6 | 34.48 (29.02–40.14) | 0.21, 29.0% | 4 | 5.26 (0.87–12.27) | 0.02, 69.4% | ||||||
Southwest provinces | 7 | 2.07 (0.85–3.69) | 0.03, 56.2% | 3 | 9.95 (0.00–38.04) | <0.01, 98.8% | ||||||
Time period | <0.01 | <0.01 | ||||||||||
–2006 | 6 | 23.10 (15.85–31.18) | 0.03, 58.8% | 4 | 3.92 (0.08–11.24) | <0.01, 75.9% | ||||||
2007–2009 | 13 | 16.98 (8.56–27.39) | <0.01, 95.6% | 8 | 3.29 (1.27–6.02) | <0.01, 70.6% | ||||||
2010–2012 | 11 | 8.62 (4.58–13.65) | <0.01, 86.1% | 7 | 7.27 (0.28–20.34) | <0.01, 96.3% | ||||||
2013–2014 | 7 | 8.52 (5.55–12.03) | <0.01, 65.7% | 4 | 0.75 (0.09–1.82) | 0.16, 41.1% | ||||||
Amplified gene region | <0.01 | <0.01 | ||||||||||
Only one | 21 | 15.19 (10.15–20.99) | <0.01, 92.1% | 13 | 2.05 (0.77–3.75) | <0.01, 65.1% | ||||||
Two or more | 16 | 10.75 (6.24–16.19) | <0.01, 90.2% | 10 | 6.83 (1.42–15.20) | <0.01, 94.8% |
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Xiao, P.; Li, J.; Fu, G.; Zhou, Y.; Huan, X.; Yang, H. Geographic Distribution and Temporal Trends of HIV-1 Subtypes through Heterosexual Transmission in China: A Systematic Review and Meta-Analysis. Int. J. Environ. Res. Public Health 2017, 14, 830. https://doi.org/10.3390/ijerph14070830
Xiao P, Li J, Fu G, Zhou Y, Huan X, Yang H. Geographic Distribution and Temporal Trends of HIV-1 Subtypes through Heterosexual Transmission in China: A Systematic Review and Meta-Analysis. International Journal of Environmental Research and Public Health. 2017; 14(7):830. https://doi.org/10.3390/ijerph14070830
Chicago/Turabian StyleXiao, Peipei, Jianjun Li, Gengfeng Fu, Ying Zhou, Xiping Huan, and Haitao Yang. 2017. "Geographic Distribution and Temporal Trends of HIV-1 Subtypes through Heterosexual Transmission in China: A Systematic Review and Meta-Analysis" International Journal of Environmental Research and Public Health 14, no. 7: 830. https://doi.org/10.3390/ijerph14070830