Prevalence and trends of transfusion-transmittable infections among blood donors in Southwest China

Prevalence and trends of transfusion-transmittable infections among blood donors in Southwest China Abstract Background The high prevalence of transfusion-transmitted infections (TTIs) is causing serious harm to human health worldwide. The aim of this research was to assess the prevalence and influencing factors of TTIs in Southwest China. Methods A retrospective study of blood donor records from January 2008 to December 2015 was conducted. All samples were screened for HBV, HCV, HIV and syphilis. The donor’s data was recorded and analyzed statistically using SPSS software. Results We revealed that the prevalence of TTIs showed a decreasing trend from 2.39 to 1.98%, and this was slightly lower than that in other regions of China. Syphilis infection was the most serious issue among blood donors in Southwest China, which demonstrated a significantly higher rate than that in other areas of China. The high infection rate of the female and farmer groups in rural regions is worth noting. The logistic regression model showed that age, occupation and donor category was the influential factors for TTIs. Conclusions The overall prevalence of TTIs demonstrated a decreasing trend from 2008 to 2015 in Southwest China, but there is still a sufficient threat to blood safety, and more efforts are needed to further guarantee blood safety in China. blood donors, HBV, HCV, HIV, syphilis Introduction Blood transfusion is an effective treatment for saving lives worldwide. It is a crucial element for surgical treatment because transfusion provides many important functions.1 However, there is a risk in transfusion caused by transfusion-transmitted infections (TTIs) through blood products from donor to recipient.2,3 The major TTIs include human immunodeficiency virus (HIV), hepatitis B virus (HBV), hepatitis C virus (HCV) and syphilis. The Joint United Nations Program on HIV/AIDS and the World Health Organization has reported that there will be 37 million HIV infections in the world by the end of 2014. To reduce the HIV prevalence, many countries had fully implemented policy decisions for prevention interventions and providing realistic care and treatment. However, the HIV prevalence showed an annual increase over the last few years in global.4,5 Although HBV (and C) virus control measures were effective, HBV (and C) is still prevalent in many countries.6–9 Additionally, syphilis prevalence has sharply increased in the general population and first-time donors during recent years, which is consistent with the prevalence in China.10,11 Previous studies have demonstrated that the high prevalence of TTIs in the general population is an enormous hazard to blood safety, and many infectious cases were found to be associated with blood transfusion.12–14 It is indicated that TTIs are still a serious threat to public health and are an important limiting factor for improving blood safety. To overcome these limits, many governments have made substantial efforts to strengthen the management of blood examinations and supplies in recent years. A precise assessment of TTI infection will contribute to developing new screening methods, monitoring transfusion safety and estimating public health policy. Therefore, it is necessary that an accurate evaluation is investigated for monitoring the prevalence of TTIs in blood donors. Despite a series of relative studies, the revealing data were limited due to population mobility and infectious diseases profile transfers. Hence, we analyzed 154 038 individual screenings of donors in Southwest China between 2008 and 2015. This study not only provided a valuable indicator to measure the safety of the blood supply and the potential risk of TTIs, but also helped to formulate and assess public health policy in China. Methods Ethical statements This study was approved by the Ethics Committee of Southwest Hospital, Third Military Medical University, Chongqing, China. Written informed consent was obtained from all participants before the interview and venous blood collection. All participants were informed that their blood samples would be tested for TTIs and they would receive the results after testing. A code used to replace the donor names, and any results were kept strictly confidential in protection of participant privacy rights. Data collection In this study, the blood center site was located in Chongqing and the unpaid donation data of 154 038 individuals were recorded in this center between 1 January 2008 and 31 December 2015. According to the current criteria of Chinese national blood donation, volunteers are necessary to validate eligibility before blood donations as follows: age between 18 and 55 years; male weight >50 kg and female weight >45 kg; the physically and mentally fit were allowed to donate blood. The medical and socio-demographic histories of participants were recorded in the center database. Pre-donation testing Either first-time donors or repeat donors (with a history of blood donation and an interval of more than 183 days) were required to pass pre-donation testing procedures, including a health history interview, a brief physical examination and rapid testing. Donation histories, medical histories and risk behavior were collected using the health history questionnaire; weight, temperature, blood pressure and heart rate was detected; rapid testing contained four parts: ABO blood type (Shanghai Hemo-pharmaceutical & Biological Co. Ltd, China), Rh blood type (EMD Millipore Co. Ltd, USA), Alanine aminotransferase (Acon Biotech Co. Ltd, China) and Hepatitis B surface antigen (HBsAg; Asintec Technology Co. Ltd, China). If there was any abnormal result in pre-donation testing, the donation was canceled; if all was normal, the donation would continue. Sample collection Blood samples were collected in 5-ml vacutainers from volunteers by venipuncture (Kehua Bio-engineering Co. Ltd, China) and stored at 4°C. Serum was separated by centrifugation at 3000 × g for 5 min and then used for screening. Serology screening All blood samples were tested using enzyme linked immunosorbent assays (ELISA) using the Microlab STAR system and the FAME system (Hamilton Co. Ltd, Switzerland). Every sample was tested twice by different staff members, and then the test procedure was repeated using another reagent, which was produced by various manufacturers. In accordance with standard operating procedures, HBsAg (Abbott Pharmaceutical Co. Ltd, USA; Asintec Technology Co. Ltd, China), anti-HCV (Abbott Pharmaceutical Co. Ltd, USA; Asintec Technology Co. Ltd, China), anti-HIV-1/2 (Beijing WANTAI Biological Pharmacy Enterprise Co. Ltd, China; BIO-RAD Laboratories Co. Ltd, USA) and anti-TP (Beijing WANTAI Biological Pharmacy Enterprise Co. Ltd, China; Beijing BGI-GBI Biotech Co. Ltd, China) were included in the test. If all the TTI results were negative, the sample was considered negative. If any screening test was positive, the following confirmatory tests were performed on the sample: HBsAg neutralization test for HBV; recombinant strip immunologic assay (RIBA) for HCV; Treponema pallidum haemagglutination assay (TPHA) for syphilis and western blotting (WB) for HIV. The final result of screening was determined by the confirmatory test. Statistical analysis Statistical analysis was conducted using SPSS for Windows 16.0. The Chi-square test was applied to evaluate the categorical variants. Odds ratios (OR) and 95% confidence intervals (CI) were calculated for all associations. The logistic regression analysis was used for assessing the influence factors of TTIs, and the independent variables included gender, age, ethnic group, marital status, occupation, education level and donation category. A P value <0.05 was used as the cut-off level for significance. Results Participant characteristics A total of 154 038 blood donors were recorded in the center from 1 January 2008 to 31 December 2015 (Table 1). Among the findings, 44.77% were females and 55.23% were males, and 69.19% were aged 18–34 years, and most were Han Chinese. Additionally, the number of married donors was slightly higher than single donors, and only 0.96% was separated/divorced/widowed. Approximately 58.42% of donors had a college degree or higher level education, and 40.46% had a high school education. Of these, students comprised the largest proportion of donors. The number of first-time donors was higher than repeat donors. Generally, most blood donors were concentrated in the young people group and higher education group. Table 1 The demographic characteristics of blood donors Variable  No. of donors (%)  Gender   Male  85 068 (55.23)   Female  68 970 (44.77)  Age   18–24  40 880 (26.54)   25–29  41 363 (26.85)   30–34  24 342 (15.80)   35–39  21 273 (13.81)   40–44  12 806 (8.31)   45–49  11 100 (7.21)   50–55  2274 (1.48)  Ethnic group   Han Chinese  152 377 (98.92)   Ethnic minorities  1661 (1.08)  Marital status   Single  75 547 (49.04)   Married  77 013 (50.00)   Separated/divorced/widowed  1478 (0.96)  Occupation   Student  60 648 (39.37)   Technology worker  21 214 (13.77)   Farmers  13 320 (8.65)   Businessman  12 848 (8.34)   Health worker  3312 (2.15)   Public officials  6671 (4.33)   Others  36 025 (23.39)  Education level   University education  89 988 (58.42)   Secondary education  62 325 (40.46)   Primary education  1725 (1.12)  Donor status   First-time donor  90 359 (58.66)   Repeat donor  63 679 (41.34)  Variable  No. of donors (%)  Gender   Male  85 068 (55.23)   Female  68 970 (44.77)  Age   18–24  40 880 (26.54)   25–29  41 363 (26.85)   30–34  24 342 (15.80)   35–39  21 273 (13.81)   40–44  12 806 (8.31)   45–49  11 100 (7.21)   50–55  2274 (1.48)  Ethnic group   Han Chinese  152 377 (98.92)   Ethnic minorities  1661 (1.08)  Marital status   Single  75 547 (49.04)   Married  77 013 (50.00)   Separated/divorced/widowed  1478 (0.96)  Occupation   Student  60 648 (39.37)   Technology worker  21 214 (13.77)   Farmers  13 320 (8.65)   Businessman  12 848 (8.34)   Health worker  3312 (2.15)   Public officials  6671 (4.33)   Others  36 025 (23.39)  Education level   University education  89 988 (58.42)   Secondary education  62 325 (40.46)   Primary education  1725 (1.12)  Donor status   First-time donor  90 359 (58.66)   Repeat donor  63 679 (41.34)  Table 1 The demographic characteristics of blood donors Variable  No. of donors (%)  Gender   Male  85 068 (55.23)   Female  68 970 (44.77)  Age   18–24  40 880 (26.54)   25–29  41 363 (26.85)   30–34  24 342 (15.80)   35–39  21 273 (13.81)   40–44  12 806 (8.31)   45–49  11 100 (7.21)   50–55  2274 (1.48)  Ethnic group   Han Chinese  152 377 (98.92)   Ethnic minorities  1661 (1.08)  Marital status   Single  75 547 (49.04)   Married  77 013 (50.00)   Separated/divorced/widowed  1478 (0.96)  Occupation   Student  60 648 (39.37)   Technology worker  21 214 (13.77)   Farmers  13 320 (8.65)   Businessman  12 848 (8.34)   Health worker  3312 (2.15)   Public officials  6671 (4.33)   Others  36 025 (23.39)  Education level   University education  89 988 (58.42)   Secondary education  62 325 (40.46)   Primary education  1725 (1.12)  Donor status   First-time donor  90 359 (58.66)   Repeat donor  63 679 (41.34)  Variable  No. of donors (%)  Gender   Male  85 068 (55.23)   Female  68 970 (44.77)  Age   18–24  40 880 (26.54)   25–29  41 363 (26.85)   30–34  24 342 (15.80)   35–39  21 273 (13.81)   40–44  12 806 (8.31)   45–49  11 100 (7.21)   50–55  2274 (1.48)  Ethnic group   Han Chinese  152 377 (98.92)   Ethnic minorities  1661 (1.08)  Marital status   Single  75 547 (49.04)   Married  77 013 (50.00)   Separated/divorced/widowed  1478 (0.96)  Occupation   Student  60 648 (39.37)   Technology worker  21 214 (13.77)   Farmers  13 320 (8.65)   Businessman  12 848 (8.34)   Health worker  3312 (2.15)   Public officials  6671 (4.33)   Others  36 025 (23.39)  Education level   University education  89 988 (58.42)   Secondary education  62 325 (40.46)   Primary education  1725 (1.12)  Donor status   First-time donor  90 359 (58.66)   Repeat donor  63 679 (41.34)  Prevalence and trend of TTIs among blood donors Compared with 2008, the number of blood donors increased by 33.37% in 2015. It shows that there was an annual increase in blood donation. As revealed in Table 2, positive TTI tests were found in 3245 people, which accounted for 2.11% of all donors. The positive rates of HBsAg, anti-HCV, anti-TP and anti-HIV-1/2 were 0.59, 0.30, 0.99 and 0.23%, respectively. The prevalence of TTIs decreased from 2.39% in 2008 to 1.84% in 2010 but followed a sharp increase to 2.56% in 2011 and then decreased to 1.98% in 2015. In brief, the overall prevalence of TTIs showed a decreasing trend during the past 8 years. Table 2 Positivity rate of transfusion-transmittable infections in blood donors Years  No. of donors  HBsAg  Anti-HCV  Anti-TP  Anti-HIV  Total  Positive rate (%)  95% CIa  Positive rate (%)  95% CI  Positive rate (%)  95% CI  Positive rate (%)  95% CI  Positive rate (%)  95% CI  2008  14 987  0.60  0.48–0.72  0.31  0.22–0.40  1.19  1.02–1.36  0.29  0.20–0.38  2.39  2.14–2.64  2009  16 156  0.61  0.49–0.73  0.15  0.09–0.21  1.08  0.92–1.24  0.33  0.24–0.42  2.17  1.94–2.40  2010  17 581  0.57  0.46–0.68  0.24  0.17–0.31  0.85  0.71–0.99  0.18  0.12–0.24  1.84  1.64–2.04  2011  19 987  0.66  0.55–0.77  0.43  0.34–0.52  1.29  1.13–1.45  0.19  0.13–0.25  2.56  2.34–2.78  2012  20 051  0.67  0.56–0.78  0.40  0.31–0.49  0.96  0.82–1.10  0.25  0.18–0.32  2.28  2.07–2.49  2013  21 232  0.57  0.47–0.67  0.14  0.09–0.19  0.88  0.75–1.01  0.16  0.10–0.21  1.74  1.56–1.92  2014  24 056  0.57  0.47–0.67  0.30  0.23–0.37  0.89  0.77–1.01  0.24  0.18–0.30  1.99  1.81–2.17  2015  19 988  0.50  0.40–0.60  0.42  0.33–0.51  0.84  0.71–0.97  0.23  0.16–0.30  1.98  1.79–2.17  P-valueb    0.38  0.00  0.00  0.01  0.00  Total  154 038  0.59  0.55–0.63  0.30  0.27–0.33  0.99  0.94–1.04  0.23  0.21–0.25  2.11  2.04–2.18  Years  No. of donors  HBsAg  Anti-HCV  Anti-TP  Anti-HIV  Total  Positive rate (%)  95% CIa  Positive rate (%)  95% CI  Positive rate (%)  95% CI  Positive rate (%)  95% CI  Positive rate (%)  95% CI  2008  14 987  0.60  0.48–0.72  0.31  0.22–0.40  1.19  1.02–1.36  0.29  0.20–0.38  2.39  2.14–2.64  2009  16 156  0.61  0.49–0.73  0.15  0.09–0.21  1.08  0.92–1.24  0.33  0.24–0.42  2.17  1.94–2.40  2010  17 581  0.57  0.46–0.68  0.24  0.17–0.31  0.85  0.71–0.99  0.18  0.12–0.24  1.84  1.64–2.04  2011  19 987  0.66  0.55–0.77  0.43  0.34–0.52  1.29  1.13–1.45  0.19  0.13–0.25  2.56  2.34–2.78  2012  20 051  0.67  0.56–0.78  0.40  0.31–0.49  0.96  0.82–1.10  0.25  0.18–0.32  2.28  2.07–2.49  2013  21 232  0.57  0.47–0.67  0.14  0.09–0.19  0.88  0.75–1.01  0.16  0.10–0.21  1.74  1.56–1.92  2014  24 056  0.57  0.47–0.67  0.30  0.23–0.37  0.89  0.77–1.01  0.24  0.18–0.30  1.99  1.81–2.17  2015  19 988  0.50  0.40–0.60  0.42  0.33–0.51  0.84  0.71–0.97  0.23  0.16–0.30  1.98  1.79–2.17  P-valueb    0.38  0.00  0.00  0.01  0.00  Total  154 038  0.59  0.55–0.63  0.30  0.27–0.33  0.99  0.94–1.04  0.23  0.21–0.25  2.11  2.04–2.18  a95% Confidence interval. bChi-square test to examine the change of trend. Table 2 Positivity rate of transfusion-transmittable infections in blood donors Years  No. of donors  HBsAg  Anti-HCV  Anti-TP  Anti-HIV  Total  Positive rate (%)  95% CIa  Positive rate (%)  95% CI  Positive rate (%)  95% CI  Positive rate (%)  95% CI  Positive rate (%)  95% CI  2008  14 987  0.60  0.48–0.72  0.31  0.22–0.40  1.19  1.02–1.36  0.29  0.20–0.38  2.39  2.14–2.64  2009  16 156  0.61  0.49–0.73  0.15  0.09–0.21  1.08  0.92–1.24  0.33  0.24–0.42  2.17  1.94–2.40  2010  17 581  0.57  0.46–0.68  0.24  0.17–0.31  0.85  0.71–0.99  0.18  0.12–0.24  1.84  1.64–2.04  2011  19 987  0.66  0.55–0.77  0.43  0.34–0.52  1.29  1.13–1.45  0.19  0.13–0.25  2.56  2.34–2.78  2012  20 051  0.67  0.56–0.78  0.40  0.31–0.49  0.96  0.82–1.10  0.25  0.18–0.32  2.28  2.07–2.49  2013  21 232  0.57  0.47–0.67  0.14  0.09–0.19  0.88  0.75–1.01  0.16  0.10–0.21  1.74  1.56–1.92  2014  24 056  0.57  0.47–0.67  0.30  0.23–0.37  0.89  0.77–1.01  0.24  0.18–0.30  1.99  1.81–2.17  2015  19 988  0.50  0.40–0.60  0.42  0.33–0.51  0.84  0.71–0.97  0.23  0.16–0.30  1.98  1.79–2.17  P-valueb    0.38  0.00  0.00  0.01  0.00  Total  154 038  0.59  0.55–0.63  0.30  0.27–0.33  0.99  0.94–1.04  0.23  0.21–0.25  2.11  2.04–2.18  Years  No. of donors  HBsAg  Anti-HCV  Anti-TP  Anti-HIV  Total  Positive rate (%)  95% CIa  Positive rate (%)  95% CI  Positive rate (%)  95% CI  Positive rate (%)  95% CI  Positive rate (%)  95% CI  2008  14 987  0.60  0.48–0.72  0.31  0.22–0.40  1.19  1.02–1.36  0.29  0.20–0.38  2.39  2.14–2.64  2009  16 156  0.61  0.49–0.73  0.15  0.09–0.21  1.08  0.92–1.24  0.33  0.24–0.42  2.17  1.94–2.40  2010  17 581  0.57  0.46–0.68  0.24  0.17–0.31  0.85  0.71–0.99  0.18  0.12–0.24  1.84  1.64–2.04  2011  19 987  0.66  0.55–0.77  0.43  0.34–0.52  1.29  1.13–1.45  0.19  0.13–0.25  2.56  2.34–2.78  2012  20 051  0.67  0.56–0.78  0.40  0.31–0.49  0.96  0.82–1.10  0.25  0.18–0.32  2.28  2.07–2.49  2013  21 232  0.57  0.47–0.67  0.14  0.09–0.19  0.88  0.75–1.01  0.16  0.10–0.21  1.74  1.56–1.92  2014  24 056  0.57  0.47–0.67  0.30  0.23–0.37  0.89  0.77–1.01  0.24  0.18–0.30  1.99  1.81–2.17  2015  19 988  0.50  0.40–0.60  0.42  0.33–0.51  0.84  0.71–0.97  0.23  0.16–0.30  1.98  1.79–2.17  P-valueb    0.38  0.00  0.00  0.01  0.00  Total  154 038  0.59  0.55–0.63  0.30  0.27–0.33  0.99  0.94–1.04  0.23  0.21–0.25  2.11  2.04–2.18  a95% Confidence interval. bChi-square test to examine the change of trend. Moreover, our results show that the number of syphilis infection cases was the highest among all TTIs. The highest positive rate of syphilis was 1.29% in 2011 and the lowest was 0.84% in 2015 (P < 0.01), and the number of positive syphilis cases showed a fluctuating trend, which was similar to the overall prevalence. Additionally, both HCV and HIV prevalence revealed a general trend of fluctuations. The positive rate of HCV ranged from 0.14 to 0.43% (P < 0.01), and the positive rate of HIV varied in a range between 0.16 and 0.33% (P < 0.01). However, in comparing syphilis, HCV and HIV, the trends differed. In TTIs, the positive cases of HBV varied between 0.50 and 0.67% (P = 0.38). HBV prevalence revealed a steady trend and barely changed in this period. The demographic characteristics of positive TTIs The characteristics of the positive TTI crowd were classified and analyzed statistically in Table 3. Our results showed that the positive rate of females (2.23%) was higher than that of males (2.01%) in overall TTI prevalence. The percentage of female syphilis cases was much higher than that of males, and the difference was significant (P < 0.01). However, HBV, HCV and HIV infections did not significantly differ between genders (P > 0.05). The HCV and HIV infection cases were more distributed in the 18–24 age group (0.57 and 0.42%, respectively), and HBV and syphilis infections were more distributed in the 40–44 (0.75%) and 45–55 age groups (2.09%), respectively. The higher TTIs infection rates were concentrated in the younger and higher aged groups. Although the separated/divorced/widowed group accounted for only 0.96% of all donors, their positive rate of TTI infection was the highest, reaching 6.02%. Specifically, the positive rate of syphilis reached 3.59% in this group, and the rate was much higher than the single (0.53%) and married (1.38%) groups. Students were accounts for 39.37% in total. However, the positive infection rate of students was only 0.84%, and it was the lowest value in the entire list. Furthermore, the highest positive rate of HBV and syphilis was in the farmer group (1.67 and 2.73%, respectively), and the highest rate of HCV and HIV infections was in the public officials group (0.69 and 0.61%, respectively). Most donors were educated beyond the primary level, but the highest prevalence of TTIs occurred in donors with only a primary education. Both donor number and TTI positive rate in first-time donors were higher than repeat donors. The results lead us to the conclusion that the TTI with the highest prevalence was syphilis among blood donors in Southwest China between 2008 and 2015, and the highest positive rate of TTIs occurred in females, aged 45–55, separated/divorced/widowed people, farmers, primary education level and first-time donors. Table 3 Positivity rate of TTIs by demographic characteristics Variable  No. of donors  HBsAg  Anti-HCV  Anti-TP  Anti-HIV  Total  Positive rate (%)  95% CIa  Positive rate (%)  95% CI  Positive rate (%)  95% CI  Positive rate  95% CI  Positive rate  95% CI  Gender   Male  85 068  0.59  0.54–0.64  0.32  0.28–0.36  0.87  0.81–0.93  0.22  0.19–0.25  2.01  1.91–2.11   Female  68 970  0.59  0.53–0.65  0.27  0.23–0.31  1.13  1.05–1.21  0.24  0.20–0.28  2.23  2.12–2.34   P-valueb    0.97  0.07  0.00  0.50  0.00  Age   18–24  40 880  0.69  0.61–0.77  0.57  0.50–0.64  0.50  0.43–0.57  0.42  0.36–0.48  2.19  2.05–2.33   25–29  41 363  0.44  0.38–0.50  0.20  0.16–0.24  0.62  0.54–0.70  0.17  0.13–0.21  1.42  1.30–1.54   30–34  24 342  0.53  0.44–0.62  0.17  0.12–0.22  0.97  0.85–1.09  0.15  0.10–0.20  1.82  1.65–1.99   35–39  21 273  0.62  0.51–0.73  0.18  0.12–0.24  1.34  1.18–1.50  0.14  0.09–0.19  2.28  2.08–2.48   40–44  12 806  0.75  0.60–0.90  0.26  0.17–0.35  2.01  1.77–2.25  0.16  0.09–0.23  3.17  2.86–3.48   45–55  13 374  0.69  0.55–0.83  0.27  0.18–0.36  2.09  1.85–2.33  0.17  0.10–0.24  3.22  2.92–3.52   P-value    0.00  0.00  0.00  0.00  0.00  Marital status   Single  75 547  0.57  0.52–0.62  0.41  0.36–0.46  0.53  0.48–0.58  0.30  0.26–0.34  1.81  1.71–1.91   Married  77 013  0.59  0.54–0.64  0.19  0.16–0.22  1.38  1.30–1.46  0.15  0.12–0.18  2.32  2.21–2.43   Separated/divorced/widowed  1478  1.42  0.81–2.03  0.47  0.12–0.82  3.59  2.63–4.55  0.54  0.17–0.91  6.02  4.78–7.26   P-value    0.00  0.00  0.00  0.00  0.00  Occupation   Student  60 648  0.29  0.25–0.33  0.19  0.16–0.22  0.26  0.22–0.30  0.11  0.08–0.14  0.84  0.77–0.91   Technology worker  21 214  0.86  0.74–0.98  0.43  0.34–0.52  1.95  1.76–2.14  0.29  0.22–0.36  3.53  3.28–3.78   Farmers  13 320  1.67  1.45–1.89  0.61  0.48–0.74  2.73  2.45–3.01  0.48  0.36–0.60  5.49  5.09–5.89   Businessman  12 848  0.93  0.76–1.10  0.36  0.26–0.46  2.05  1.80–2.30  0.30  0.21–0.39  3.64  3.31–3.97   Health worker  3312  0.21  0.05–0.37  0.21  0.05–0.37  0.36  0.16–0.56  0.21  0.05–0.37  1.00  0.66–1.34   Public officials  6671  1.09  0.84–1.34  0.69  0.49–0.89  1.50  1.21–1.79  0.61  0.42–0.80  3.90  3.43–4.37   Others  36 025  0.37  0.31–0.43  0.22  0.17–0.27  0.58  0.50–0.66  0.20  0.15–0.25  1.37  1.25–1.49   P-value    0.00  0.00  0.00  0.00  0.00  Education level   Primary or less  1725  2.03  1.36–2.70  0.93  0.48–1.38  3.94  3.00–4.88  0.70  0.30–1.08  7.59  6.27–8.89   Secondary  62 325  0.80  0.73–0.87  0.39  0.34–0.44  1.72  1.62–1.82  0.29  0.24–0.32  3.21  3.05–3.33   University or above  89 988  0.42  0.29–0.55  0.23  0.20–0.43  0.41  0.37–0.45  0.18  0.15–0.21  1.23  1.16–1.30   P-value    0.00  0.00  0.00  0.00  0.00  Donor category   First time  90 359  0.92  0.86–0.98  0.42  0.38–0.46  1.59  1.51–1.67  0.30  0.26–0.34  3.22  3.10–3.34   Repeated  63 679  0.13  0.10–0.16  0.13  0.10–0.16  0.13  0.10–0.16  0.13  0.10–0.16  0.52  0.46–0.58   P-value    0.00  0.00  0.00  0.00  0.00  Total  154 038  0.59  0.55–0.63  0.30  0.27–0.33  0.99  0.94–1.04  0.23  0.21–0.25  2.11  2.04–2.18  Variable  No. of donors  HBsAg  Anti-HCV  Anti-TP  Anti-HIV  Total  Positive rate (%)  95% CIa  Positive rate (%)  95% CI  Positive rate (%)  95% CI  Positive rate  95% CI  Positive rate  95% CI  Gender   Male  85 068  0.59  0.54–0.64  0.32  0.28–0.36  0.87  0.81–0.93  0.22  0.19–0.25  2.01  1.91–2.11   Female  68 970  0.59  0.53–0.65  0.27  0.23–0.31  1.13  1.05–1.21  0.24  0.20–0.28  2.23  2.12–2.34   P-valueb    0.97  0.07  0.00  0.50  0.00  Age   18–24  40 880  0.69  0.61–0.77  0.57  0.50–0.64  0.50  0.43–0.57  0.42  0.36–0.48  2.19  2.05–2.33   25–29  41 363  0.44  0.38–0.50  0.20  0.16–0.24  0.62  0.54–0.70  0.17  0.13–0.21  1.42  1.30–1.54   30–34  24 342  0.53  0.44–0.62  0.17  0.12–0.22  0.97  0.85–1.09  0.15  0.10–0.20  1.82  1.65–1.99   35–39  21 273  0.62  0.51–0.73  0.18  0.12–0.24  1.34  1.18–1.50  0.14  0.09–0.19  2.28  2.08–2.48   40–44  12 806  0.75  0.60–0.90  0.26  0.17–0.35  2.01  1.77–2.25  0.16  0.09–0.23  3.17  2.86–3.48   45–55  13 374  0.69  0.55–0.83  0.27  0.18–0.36  2.09  1.85–2.33  0.17  0.10–0.24  3.22  2.92–3.52   P-value    0.00  0.00  0.00  0.00  0.00  Marital status   Single  75 547  0.57  0.52–0.62  0.41  0.36–0.46  0.53  0.48–0.58  0.30  0.26–0.34  1.81  1.71–1.91   Married  77 013  0.59  0.54–0.64  0.19  0.16–0.22  1.38  1.30–1.46  0.15  0.12–0.18  2.32  2.21–2.43   Separated/divorced/widowed  1478  1.42  0.81–2.03  0.47  0.12–0.82  3.59  2.63–4.55  0.54  0.17–0.91  6.02  4.78–7.26   P-value    0.00  0.00  0.00  0.00  0.00  Occupation   Student  60 648  0.29  0.25–0.33  0.19  0.16–0.22  0.26  0.22–0.30  0.11  0.08–0.14  0.84  0.77–0.91   Technology worker  21 214  0.86  0.74–0.98  0.43  0.34–0.52  1.95  1.76–2.14  0.29  0.22–0.36  3.53  3.28–3.78   Farmers  13 320  1.67  1.45–1.89  0.61  0.48–0.74  2.73  2.45–3.01  0.48  0.36–0.60  5.49  5.09–5.89   Businessman  12 848  0.93  0.76–1.10  0.36  0.26–0.46  2.05  1.80–2.30  0.30  0.21–0.39  3.64  3.31–3.97   Health worker  3312  0.21  0.05–0.37  0.21  0.05–0.37  0.36  0.16–0.56  0.21  0.05–0.37  1.00  0.66–1.34   Public officials  6671  1.09  0.84–1.34  0.69  0.49–0.89  1.50  1.21–1.79  0.61  0.42–0.80  3.90  3.43–4.37   Others  36 025  0.37  0.31–0.43  0.22  0.17–0.27  0.58  0.50–0.66  0.20  0.15–0.25  1.37  1.25–1.49   P-value    0.00  0.00  0.00  0.00  0.00  Education level   Primary or less  1725  2.03  1.36–2.70  0.93  0.48–1.38  3.94  3.00–4.88  0.70  0.30–1.08  7.59  6.27–8.89   Secondary  62 325  0.80  0.73–0.87  0.39  0.34–0.44  1.72  1.62–1.82  0.29  0.24–0.32  3.21  3.05–3.33   University or above  89 988  0.42  0.29–0.55  0.23  0.20–0.43  0.41  0.37–0.45  0.18  0.15–0.21  1.23  1.16–1.30   P-value    0.00  0.00  0.00  0.00  0.00  Donor category   First time  90 359  0.92  0.86–0.98  0.42  0.38–0.46  1.59  1.51–1.67  0.30  0.26–0.34  3.22  3.10–3.34   Repeated  63 679  0.13  0.10–0.16  0.13  0.10–0.16  0.13  0.10–0.16  0.13  0.10–0.16  0.52  0.46–0.58   P-value    0.00  0.00  0.00  0.00  0.00  Total  154 038  0.59  0.55–0.63  0.30  0.27–0.33  0.99  0.94–1.04  0.23  0.21–0.25  2.11  2.04–2.18  a95% Confidence interval. bChi-square trend test to test statistical difference in the distribution with each group. Table 3 Positivity rate of TTIs by demographic characteristics Variable  No. of donors  HBsAg  Anti-HCV  Anti-TP  Anti-HIV  Total  Positive rate (%)  95% CIa  Positive rate (%)  95% CI  Positive rate (%)  95% CI  Positive rate  95% CI  Positive rate  95% CI  Gender   Male  85 068  0.59  0.54–0.64  0.32  0.28–0.36  0.87  0.81–0.93  0.22  0.19–0.25  2.01  1.91–2.11   Female  68 970  0.59  0.53–0.65  0.27  0.23–0.31  1.13  1.05–1.21  0.24  0.20–0.28  2.23  2.12–2.34   P-valueb    0.97  0.07  0.00  0.50  0.00  Age   18–24  40 880  0.69  0.61–0.77  0.57  0.50–0.64  0.50  0.43–0.57  0.42  0.36–0.48  2.19  2.05–2.33   25–29  41 363  0.44  0.38–0.50  0.20  0.16–0.24  0.62  0.54–0.70  0.17  0.13–0.21  1.42  1.30–1.54   30–34  24 342  0.53  0.44–0.62  0.17  0.12–0.22  0.97  0.85–1.09  0.15  0.10–0.20  1.82  1.65–1.99   35–39  21 273  0.62  0.51–0.73  0.18  0.12–0.24  1.34  1.18–1.50  0.14  0.09–0.19  2.28  2.08–2.48   40–44  12 806  0.75  0.60–0.90  0.26  0.17–0.35  2.01  1.77–2.25  0.16  0.09–0.23  3.17  2.86–3.48   45–55  13 374  0.69  0.55–0.83  0.27  0.18–0.36  2.09  1.85–2.33  0.17  0.10–0.24  3.22  2.92–3.52   P-value    0.00  0.00  0.00  0.00  0.00  Marital status   Single  75 547  0.57  0.52–0.62  0.41  0.36–0.46  0.53  0.48–0.58  0.30  0.26–0.34  1.81  1.71–1.91   Married  77 013  0.59  0.54–0.64  0.19  0.16–0.22  1.38  1.30–1.46  0.15  0.12–0.18  2.32  2.21–2.43   Separated/divorced/widowed  1478  1.42  0.81–2.03  0.47  0.12–0.82  3.59  2.63–4.55  0.54  0.17–0.91  6.02  4.78–7.26   P-value    0.00  0.00  0.00  0.00  0.00  Occupation   Student  60 648  0.29  0.25–0.33  0.19  0.16–0.22  0.26  0.22–0.30  0.11  0.08–0.14  0.84  0.77–0.91   Technology worker  21 214  0.86  0.74–0.98  0.43  0.34–0.52  1.95  1.76–2.14  0.29  0.22–0.36  3.53  3.28–3.78   Farmers  13 320  1.67  1.45–1.89  0.61  0.48–0.74  2.73  2.45–3.01  0.48  0.36–0.60  5.49  5.09–5.89   Businessman  12 848  0.93  0.76–1.10  0.36  0.26–0.46  2.05  1.80–2.30  0.30  0.21–0.39  3.64  3.31–3.97   Health worker  3312  0.21  0.05–0.37  0.21  0.05–0.37  0.36  0.16–0.56  0.21  0.05–0.37  1.00  0.66–1.34   Public officials  6671  1.09  0.84–1.34  0.69  0.49–0.89  1.50  1.21–1.79  0.61  0.42–0.80  3.90  3.43–4.37   Others  36 025  0.37  0.31–0.43  0.22  0.17–0.27  0.58  0.50–0.66  0.20  0.15–0.25  1.37  1.25–1.49   P-value    0.00  0.00  0.00  0.00  0.00  Education level   Primary or less  1725  2.03  1.36–2.70  0.93  0.48–1.38  3.94  3.00–4.88  0.70  0.30–1.08  7.59  6.27–8.89   Secondary  62 325  0.80  0.73–0.87  0.39  0.34–0.44  1.72  1.62–1.82  0.29  0.24–0.32  3.21  3.05–3.33   University or above  89 988  0.42  0.29–0.55  0.23  0.20–0.43  0.41  0.37–0.45  0.18  0.15–0.21  1.23  1.16–1.30   P-value    0.00  0.00  0.00  0.00  0.00  Donor category   First time  90 359  0.92  0.86–0.98  0.42  0.38–0.46  1.59  1.51–1.67  0.30  0.26–0.34  3.22  3.10–3.34   Repeated  63 679  0.13  0.10–0.16  0.13  0.10–0.16  0.13  0.10–0.16  0.13  0.10–0.16  0.52  0.46–0.58   P-value    0.00  0.00  0.00  0.00  0.00  Total  154 038  0.59  0.55–0.63  0.30  0.27–0.33  0.99  0.94–1.04  0.23  0.21–0.25  2.11  2.04–2.18  Variable  No. of donors  HBsAg  Anti-HCV  Anti-TP  Anti-HIV  Total  Positive rate (%)  95% CIa  Positive rate (%)  95% CI  Positive rate (%)  95% CI  Positive rate  95% CI  Positive rate  95% CI  Gender   Male  85 068  0.59  0.54–0.64  0.32  0.28–0.36  0.87  0.81–0.93  0.22  0.19–0.25  2.01  1.91–2.11   Female  68 970  0.59  0.53–0.65  0.27  0.23–0.31  1.13  1.05–1.21  0.24  0.20–0.28  2.23  2.12–2.34   P-valueb    0.97  0.07  0.00  0.50  0.00  Age   18–24  40 880  0.69  0.61–0.77  0.57  0.50–0.64  0.50  0.43–0.57  0.42  0.36–0.48  2.19  2.05–2.33   25–29  41 363  0.44  0.38–0.50  0.20  0.16–0.24  0.62  0.54–0.70  0.17  0.13–0.21  1.42  1.30–1.54   30–34  24 342  0.53  0.44–0.62  0.17  0.12–0.22  0.97  0.85–1.09  0.15  0.10–0.20  1.82  1.65–1.99   35–39  21 273  0.62  0.51–0.73  0.18  0.12–0.24  1.34  1.18–1.50  0.14  0.09–0.19  2.28  2.08–2.48   40–44  12 806  0.75  0.60–0.90  0.26  0.17–0.35  2.01  1.77–2.25  0.16  0.09–0.23  3.17  2.86–3.48   45–55  13 374  0.69  0.55–0.83  0.27  0.18–0.36  2.09  1.85–2.33  0.17  0.10–0.24  3.22  2.92–3.52   P-value    0.00  0.00  0.00  0.00  0.00  Marital status   Single  75 547  0.57  0.52–0.62  0.41  0.36–0.46  0.53  0.48–0.58  0.30  0.26–0.34  1.81  1.71–1.91   Married  77 013  0.59  0.54–0.64  0.19  0.16–0.22  1.38  1.30–1.46  0.15  0.12–0.18  2.32  2.21–2.43   Separated/divorced/widowed  1478  1.42  0.81–2.03  0.47  0.12–0.82  3.59  2.63–4.55  0.54  0.17–0.91  6.02  4.78–7.26   P-value    0.00  0.00  0.00  0.00  0.00  Occupation   Student  60 648  0.29  0.25–0.33  0.19  0.16–0.22  0.26  0.22–0.30  0.11  0.08–0.14  0.84  0.77–0.91   Technology worker  21 214  0.86  0.74–0.98  0.43  0.34–0.52  1.95  1.76–2.14  0.29  0.22–0.36  3.53  3.28–3.78   Farmers  13 320  1.67  1.45–1.89  0.61  0.48–0.74  2.73  2.45–3.01  0.48  0.36–0.60  5.49  5.09–5.89   Businessman  12 848  0.93  0.76–1.10  0.36  0.26–0.46  2.05  1.80–2.30  0.30  0.21–0.39  3.64  3.31–3.97   Health worker  3312  0.21  0.05–0.37  0.21  0.05–0.37  0.36  0.16–0.56  0.21  0.05–0.37  1.00  0.66–1.34   Public officials  6671  1.09  0.84–1.34  0.69  0.49–0.89  1.50  1.21–1.79  0.61  0.42–0.80  3.90  3.43–4.37   Others  36 025  0.37  0.31–0.43  0.22  0.17–0.27  0.58  0.50–0.66  0.20  0.15–0.25  1.37  1.25–1.49   P-value    0.00  0.00  0.00  0.00  0.00  Education level   Primary or less  1725  2.03  1.36–2.70  0.93  0.48–1.38  3.94  3.00–4.88  0.70  0.30–1.08  7.59  6.27–8.89   Secondary  62 325  0.80  0.73–0.87  0.39  0.34–0.44  1.72  1.62–1.82  0.29  0.24–0.32  3.21  3.05–3.33   University or above  89 988  0.42  0.29–0.55  0.23  0.20–0.43  0.41  0.37–0.45  0.18  0.15–0.21  1.23  1.16–1.30   P-value    0.00  0.00  0.00  0.00  0.00  Donor category   First time  90 359  0.92  0.86–0.98  0.42  0.38–0.46  1.59  1.51–1.67  0.30  0.26–0.34  3.22  3.10–3.34   Repeated  63 679  0.13  0.10–0.16  0.13  0.10–0.16  0.13  0.10–0.16  0.13  0.10–0.16  0.52  0.46–0.58   P-value    0.00  0.00  0.00  0.00  0.00  Total  154 038  0.59  0.55–0.63  0.30  0.27–0.33  0.99  0.94–1.04  0.23  0.21–0.25  2.11  2.04–2.18  a95% Confidence interval. bChi-square trend test to test statistical difference in the distribution with each group. Influential factors of TTIs To define the influencing factors of TTIs, a logistic regression analysis model was established (Table 4). In this model, gender, age, marital status, occupation, education level and donor category were included in the analysis, and the reference group of these variables was male, age 18–24, single, student, university level or above and first-time donors. The results show that the positive rate of transfusion-transmitted infectious diseases was independently associated with age, occupation and donor category. Table 4 Influential factors of transfusion-transmittable infectionsa Variable  P-valueb  Odds ratio  95% CIc  Age  0.00  1.14  1.11–1.16  Occupation  0.00  0.68  0.60–0.77  Donor category  0.00  0.14  0.13–0.16  Variable  P-valueb  Odds ratio  95% CIc  Age  0.00  1.14  1.11–1.16  Occupation  0.00  0.68  0.60–0.77  Donor category  0.00  0.14  0.13–0.16  aIn logistic regression analysis, the reference group of these variables was male, age 18–24, single, student, university level or above and first-time donors. bChi-square trend test to test the statistical difference in each group. c95% Confidence interval. Table 4 Influential factors of transfusion-transmittable infectionsa Variable  P-valueb  Odds ratio  95% CIc  Age  0.00  1.14  1.11–1.16  Occupation  0.00  0.68  0.60–0.77  Donor category  0.00  0.14  0.13–0.16  Variable  P-valueb  Odds ratio  95% CIc  Age  0.00  1.14  1.11–1.16  Occupation  0.00  0.68  0.60–0.77  Donor category  0.00  0.14  0.13–0.16  aIn logistic regression analysis, the reference group of these variables was male, age 18–24, single, student, university level or above and first-time donors. bChi-square trend test to test the statistical difference in each group. c95% Confidence interval. Discussion Blood transfusion is a life-saving measure. However, transfusion is an efficient mode of transmission for blood borne infections. Therefore, TTI infection assessment has great significance for clinical transfusion safety.15 Our research shows that the overall prevalence of TTIs was slightly lower in Southwest China, but the syphilis infection rate was significantly higher than that in Nanjing (0.36%), Guangzhou (0.42%), Liaoning (0.60%) and Yancheng (0.70%).16 The positive rate of syphilis was the highest among TTIs, and the rate was 0.99%, which was higher than that of HBV (0.59%), HCV (0.30%) and HIV (0.23). Additionally, females accounted for a higher percentage than males among syphilis cases. The China CDC has reported that the number of recorded cases of syphilis was 40 849 individuals at the end of 2015, and it increased by 5% compared with the last year. Notably, the infection number of females was higher than males, and the ratio was 1:0.9.17 The number of syphilis infections in the general population showed a sharp increase in recent years, and the gender differences have been presented in the data. Both the blood donors and general population with syphilis demonstrated a high prevalence trend, and the female infection rate was higher than that in males. The results may be associated with many factors, such as economic conditions and cultural and social environments. In Southwest China, the local economy is less developed than in the eastern region because of certain limitations, such as economic and public traffic. Therefore, a large amount of the labor force are in the east or other developed economic regions each year, and many women remain in the country to care for the family. Long-term separation may lead to unstable family surroundings or un-marriage sexual behavior was increased, which is accompanied by having various sexual partners, which may be associated with sexual transmission was increased.18 Additionally, sexual transmission between spouses has also increased, and this situation may cause an increase in females with syphilis infection.17 Moreover, it has been reported that the occupation with the highest syphilis rate was the farmers group among blood donors.18,19 This is the same as our results, and the highest positive rate of TTIs was in the farmers group in our study. The farmers group is a special population, and most of them live in rural areas where the culture and information is relatively behind that in the city. Thus, the population lacks awareness of TTI prevention and control. Additionally, the sexual attitudes of the population changed from closed to open, and non-marital sexual behavior increased in recent years. Thus, all these factors increased the infection risk in farmers.20,21 To reduce the prevalence of HBV infection, the central government promoted the hepatitis B vaccination in 1992 for the general population, and all newborns have been given this vaccine for free since 2005.22 Although these measures effectively reduced the prevalence of HBV, there are ~100 million infections in China.23,24 In this study, the HBV infection rate was significantly lower than in the general population (7.2%) because donations were canceled if there was a positive HBsAg in pre-donation testing. Pre-donation testing could exclude HBV infected and co-infected donors. Unfortunately, the excluded donors were not analyzed in our study because their information was too difficult to collect. This may be the reason why the results were too low, and there are no co-infected donors in our study. However, the HBV infection analysis of blood donors has a great significance for monitoring the blood donation security. A total of 3.2% of the general population has HCV in China, and ~150 million people are infected with it in the world.7 HCV was eliminated recently following a large-scale prevention and control policy in China. The positive rate of HCV was 12.87% in blood donors before 1998 and significantly decreased to 1.71% after 1998.7,25 In our study, the overall prevalence of HCV was only 0.30% in Southwest China, and the positive rate of HCV varied between 0.14 and 0.43% from 2008 to 2015. The rate was lower than that in other Chinese regions.19,26 HCV infection has a low prevalence among blood donors in Southwest China. Additionally, the number of HCV-infected males was more than that of females, but there were no significant differences between genders. This gender distribution was the same as the previous reports from Xi’an,26 Guangzhou and Nanjing,16 and different from Shiyan.18 HIV is a serious infection that endangers public health in the world. At the end of 2015, a total of 577 423 HIV/AIDS cases were reported, and the number of deaths was 182 882 in China. The number of infections in males was more than females, and sexual transmission caused the largest proportion of HIV infection.17 In this study, the HIV infection rate was 0.23% among blood donors in Southwest China. The value was higher than that in Xi’an,26 Liaoning, Guangzhou16 and Shiyan18 and lower than that in the blood donors in Western China.19 The findings were consistent with the CDC report, and HIV infection occurs mainly through sexual transmission in blood donors. However, there were no significant differences between genders. Moreover, the CDC has reported that the number of people <15 years old has increased annually in the general population,17 and our study shows that the highest infectious burden occurred in the 18–24-year group. Those who are becoming infected with HIV are increasingly younger. With improving the HIV Monitoring Network, the effective detection and management of the high-risk population is conducive to HIV/AIDS prevention.27 However, the high prevalence of HIV is still a serious threat for blood transfusion safety in China. Generally, TTIs have a high prevalence in China compared with other countries, and more efforts are needed to ensure blood safety in the long term.9,28 The government should further strengthen the spread of knowledge and information of TTI prevention, especially in rural regions, to improve the awareness of disease prevention in the general population.20,21 Additionally, intervention management of the high-risk population should be further increased to achieve better disease control. The standard blood collection and screening process needs further improvement for guaranteeing blood safety. In standard Chinese procedures, TTI detection was occurred using ELISA, and the ‘window period’ of this method is between 2 weeks and 3 months. Given that testing is confined to serologic testing, there remains risk of transmission of incident TTIs in the pre-seroconversion window period.29,30 Therefore, many countries have adopted nucleic acid testing (NAT) for screening because NAT has the ability to shorten the ‘window period’ for reducing TTI residual risks.9,28 At present, NAT was only used at the larger blood centers in China because it was limited by high cost and people with advanced training. To improve the application of NAT, the Chinese government has formulated an effective policy for helping all blood centers to complete the detection system. These measures would help to reduce the prevalence of TTIs and ensure the safety of the blood supply in the long term. Acknowledgements The authors gratefully acknowledge all the staff members of the blood center for their support during data collection. References 1 Seitz R, Heiden M. Quality and safety in blood supply in 2010. Transfus Med Hemother  2010; 37( 3): 112– 7. Google Scholar CrossRef Search ADS PubMed  2 Luban NL. Transfusion safety: where are we today? Ann NY Acad Sci  2005; 1054: 325– 41. Google Scholar CrossRef Search ADS PubMed  3 Bönig H, Schmidt M, Hourfar K et al.  . Sufficient blood, safe blood: can we have both? BMC Med  2012; 10: 29. Google Scholar CrossRef Search ADS PubMed  4 Ministry of Health of China, World Health Organization, Joint United Nations Programme on HIV/AIDS. 2005 Update on the HIV/AIDS Epidemic and Response in China. Beijing: Ministry of Health 2006. 5 Ministry of Health of China, World Health Organization, Joint United Nations Programme on HIV/AIDS. 2014 Update on the HIV/AIDS Epidemic and Response in China. Beijing: Ministry of Health 2015. 6 Guo XC, Wu YQ. A review: progress of prevention and control of viral hepatitis in China. Biomed Environ Sci  1999; 12( 3): 227– 32. Google Scholar PubMed  7 Gao XF, Cui Q, Shi X et al.  . Prevalence and trend of hepatitis C virus infection among blood donors in Chinese mainland: a systematic review and metamorphosis. BMC Infect Dis  2012; 11: 88. Google Scholar CrossRef Search ADS   8 Seo DH, Whang DH, Song EY et al.  . Occult hepatitis B virus infection and blood transfusion. World J Hepatol  2015; 7( 3): 600– 6. Google Scholar CrossRef Search ADS PubMed  9 Kim MJ, Park Q, Min HK et al.  . Residual risk of transfusion-transmitted infection with human immunodeficiency virus, hepatitis C virus, and hepatitis B virus in Korea from 2000 through 2010. BMC Infect Dis  2012; 12: 160. Google Scholar CrossRef Search ADS PubMed  10 Chen ZQ, Zhang GC, Gong XD et al.  . Syphilis in China: results of a national surveillance programme. Lancet  2007; 369( 9556): 132– 8. Google Scholar CrossRef Search ADS PubMed  11 Liu J, Huang Y, Wang JX et al.  . The increasing prevalence of serologic markers for syphilis among Chinese blood donors in 2008 through 2010 during a syphilis epidemic. Transfusion  2012; 52( 8): 1741– 9. Google Scholar CrossRef Search ADS PubMed  12 Erwin K. The circulatory system: blood procurement, AIDS, and the social body in China. Med Anthropol Q  2006; 20( 2): 139– 59. Google Scholar CrossRef Search ADS PubMed  13 Adams V, Erwin K, Le PV. Public health works: blood donation in urban China. Soc Sci Med  2009; 68( 3): 410– 8. Google Scholar CrossRef Search ADS PubMed  14 Shan H, Wang JX, Ren FR et al.  . Blood banking in China. Lancet  2002; 360( 9347): 1770– 5. Google Scholar CrossRef Search ADS PubMed  15 Glynn SA, Busch MP, Schreiber GB et al.  . Effect of a national disaster on blood supply and safety: the September 11 experience. J Am Med Assoc  2003; 289( 17): 2246– 53. Google Scholar CrossRef Search ADS   16 Li C, Xiao X, Yin H et al.  . Prevalence and prevalence trends of transfusion transmissible infections among blood donors at four Chinese regional blood centers between 2000 and 2010. J Transl Med  2012; 10: 176. Google Scholar CrossRef Search ADS PubMed  17 National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention. Update on the AIDS/STD epidemic in China and main response in control and prevention in December, 2015. Chin J AIDS STD  2016; 22( 2): 69. 18 Yang SG, Jiao DM, Liu CJ et al.  . Serioprevalence of human immunodeficiency virus, hepatitis B and C viruses, and Treponema pallidum infections among blood donors at Shiyan, Central China. BMC Infect Dis  2016; 16: 531. Google Scholar CrossRef Search ADS PubMed  19 Song Y, Bian Y, Petzold M et al.  . Prevalence and trend of major transfusion-transmissible infections among blood donors in Western China, 2005 through 2010. PLOS One  2014; 9( 4): e94528. Google Scholar CrossRef Search ADS PubMed  20 Dong R, Qiao X, Jia W et al.  . HIV, HCV, and HBV co-infections in a rural area of Shanxi province with a history of commercial blood donation. Biomed Environ Sci  2011; 24( 3): 207– 13. Google Scholar PubMed  21 Zaller N, Nelson KE, Ness P et al.  . Demographic characteristics and risks for transfusion-transmissible infection among blood donors in Xinjiang autonomous region, People’s Republic of China. Transfusion  2006; 46( 2): 265– 71. Google Scholar CrossRef Search ADS PubMed  22 Liang XF, Bi SL, Yang WZ et al.  . Evaluation of the impact of hepatitis B vaccination among children born during 1992–2005 in China. J Infect Dis  2009; 200( 1): 39– 47. Google Scholar CrossRef Search ADS PubMed  23 Liang XF, Bi SL, Yang WZ et al.  . Epidemiological serosurvey of hepatitis B in China declining HBV prevalence due to hepatitis B vaccination. Vaccine  2009; 27( 47): 6550– 7. Google Scholar CrossRef Search ADS PubMed  24 Luo Z, Li L, Ruan B. Impact of the implementation of a vaccination strategy on hepatitis B virus infections in China over a 20-year period. Int J Infect Dis  2012; 16( 2): e82– 8. Google Scholar CrossRef Search ADS PubMed  25 Fu Y, Wang Y, Xia W et al.  . New trends of HCV infection in China revealed by genetic analysis of viral sequences determined from first-time volunteer blood donors. J Viral Hepat  2011; 18( 1): 42– 52. Google Scholar CrossRef Search ADS PubMed  26 Ji ZH, Li CY, Lv YG et al.  . The prevalence and trends of transfusion-transmissible infectious pathogens among first-time, voluntary blood donors in Xi’an, China between 1999 and 2009. Int J Infect Dis  2013; 17( 4): 259– 62. Google Scholar CrossRef Search ADS   27 Wang LD. Overview of the HIV/AIDS epidemic, scientific research and government responses in China. AIDS  2007; 21( Suppl 8): S3– 7. Google Scholar CrossRef Search ADS PubMed  28 Tani Y, Aso H, Matsukura H et al.  . Significant background rates of HBV and HCV infections in patients and risks of blood transfusion from donors with low anti-HBc titres or high anti-HBc titres with high anti-HBs titres in Japan: a prospective, individual NAT study of transfusion-transmitted HBV, HCV and HIV infections. Vox Sang  2012; 102( 4): 285– 93. Google Scholar CrossRef Search ADS PubMed  29 Bruhn R, Lelie N, Busch M et al.  . Relative efficacy of nucleic acid amplification testing and serologic screening in preventing hepatitis C virus transmission risk in seven international regions. Transfusion  2015; 55( 6): 1195– 205. Google Scholar CrossRef Search ADS PubMed  30 De Souza MS, Phanuphak N, Pinyakorn S et al.  . Impact of nucleic acid testing relative to antigen/antibody combination immunoassay on the detection of acute HIV infection. AIDS  2015; 29( 7): 793– 800. Google Scholar CrossRef Search ADS PubMed  © The Author(s) 2018. Published by Oxford University Press on behalf of Faculty of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Public Health Oxford University Press

Prevalence and trends of transfusion-transmittable infections among blood donors in Southwest China

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10.1093/pubmed/fdx189
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Abstract

Abstract Background The high prevalence of transfusion-transmitted infections (TTIs) is causing serious harm to human health worldwide. The aim of this research was to assess the prevalence and influencing factors of TTIs in Southwest China. Methods A retrospective study of blood donor records from January 2008 to December 2015 was conducted. All samples were screened for HBV, HCV, HIV and syphilis. The donor’s data was recorded and analyzed statistically using SPSS software. Results We revealed that the prevalence of TTIs showed a decreasing trend from 2.39 to 1.98%, and this was slightly lower than that in other regions of China. Syphilis infection was the most serious issue among blood donors in Southwest China, which demonstrated a significantly higher rate than that in other areas of China. The high infection rate of the female and farmer groups in rural regions is worth noting. The logistic regression model showed that age, occupation and donor category was the influential factors for TTIs. Conclusions The overall prevalence of TTIs demonstrated a decreasing trend from 2008 to 2015 in Southwest China, but there is still a sufficient threat to blood safety, and more efforts are needed to further guarantee blood safety in China. blood donors, HBV, HCV, HIV, syphilis Introduction Blood transfusion is an effective treatment for saving lives worldwide. It is a crucial element for surgical treatment because transfusion provides many important functions.1 However, there is a risk in transfusion caused by transfusion-transmitted infections (TTIs) through blood products from donor to recipient.2,3 The major TTIs include human immunodeficiency virus (HIV), hepatitis B virus (HBV), hepatitis C virus (HCV) and syphilis. The Joint United Nations Program on HIV/AIDS and the World Health Organization has reported that there will be 37 million HIV infections in the world by the end of 2014. To reduce the HIV prevalence, many countries had fully implemented policy decisions for prevention interventions and providing realistic care and treatment. However, the HIV prevalence showed an annual increase over the last few years in global.4,5 Although HBV (and C) virus control measures were effective, HBV (and C) is still prevalent in many countries.6–9 Additionally, syphilis prevalence has sharply increased in the general population and first-time donors during recent years, which is consistent with the prevalence in China.10,11 Previous studies have demonstrated that the high prevalence of TTIs in the general population is an enormous hazard to blood safety, and many infectious cases were found to be associated with blood transfusion.12–14 It is indicated that TTIs are still a serious threat to public health and are an important limiting factor for improving blood safety. To overcome these limits, many governments have made substantial efforts to strengthen the management of blood examinations and supplies in recent years. A precise assessment of TTI infection will contribute to developing new screening methods, monitoring transfusion safety and estimating public health policy. Therefore, it is necessary that an accurate evaluation is investigated for monitoring the prevalence of TTIs in blood donors. Despite a series of relative studies, the revealing data were limited due to population mobility and infectious diseases profile transfers. Hence, we analyzed 154 038 individual screenings of donors in Southwest China between 2008 and 2015. This study not only provided a valuable indicator to measure the safety of the blood supply and the potential risk of TTIs, but also helped to formulate and assess public health policy in China. Methods Ethical statements This study was approved by the Ethics Committee of Southwest Hospital, Third Military Medical University, Chongqing, China. Written informed consent was obtained from all participants before the interview and venous blood collection. All participants were informed that their blood samples would be tested for TTIs and they would receive the results after testing. A code used to replace the donor names, and any results were kept strictly confidential in protection of participant privacy rights. Data collection In this study, the blood center site was located in Chongqing and the unpaid donation data of 154 038 individuals were recorded in this center between 1 January 2008 and 31 December 2015. According to the current criteria of Chinese national blood donation, volunteers are necessary to validate eligibility before blood donations as follows: age between 18 and 55 years; male weight >50 kg and female weight >45 kg; the physically and mentally fit were allowed to donate blood. The medical and socio-demographic histories of participants were recorded in the center database. Pre-donation testing Either first-time donors or repeat donors (with a history of blood donation and an interval of more than 183 days) were required to pass pre-donation testing procedures, including a health history interview, a brief physical examination and rapid testing. Donation histories, medical histories and risk behavior were collected using the health history questionnaire; weight, temperature, blood pressure and heart rate was detected; rapid testing contained four parts: ABO blood type (Shanghai Hemo-pharmaceutical & Biological Co. Ltd, China), Rh blood type (EMD Millipore Co. Ltd, USA), Alanine aminotransferase (Acon Biotech Co. Ltd, China) and Hepatitis B surface antigen (HBsAg; Asintec Technology Co. Ltd, China). If there was any abnormal result in pre-donation testing, the donation was canceled; if all was normal, the donation would continue. Sample collection Blood samples were collected in 5-ml vacutainers from volunteers by venipuncture (Kehua Bio-engineering Co. Ltd, China) and stored at 4°C. Serum was separated by centrifugation at 3000 × g for 5 min and then used for screening. Serology screening All blood samples were tested using enzyme linked immunosorbent assays (ELISA) using the Microlab STAR system and the FAME system (Hamilton Co. Ltd, Switzerland). Every sample was tested twice by different staff members, and then the test procedure was repeated using another reagent, which was produced by various manufacturers. In accordance with standard operating procedures, HBsAg (Abbott Pharmaceutical Co. Ltd, USA; Asintec Technology Co. Ltd, China), anti-HCV (Abbott Pharmaceutical Co. Ltd, USA; Asintec Technology Co. Ltd, China), anti-HIV-1/2 (Beijing WANTAI Biological Pharmacy Enterprise Co. Ltd, China; BIO-RAD Laboratories Co. Ltd, USA) and anti-TP (Beijing WANTAI Biological Pharmacy Enterprise Co. Ltd, China; Beijing BGI-GBI Biotech Co. Ltd, China) were included in the test. If all the TTI results were negative, the sample was considered negative. If any screening test was positive, the following confirmatory tests were performed on the sample: HBsAg neutralization test for HBV; recombinant strip immunologic assay (RIBA) for HCV; Treponema pallidum haemagglutination assay (TPHA) for syphilis and western blotting (WB) for HIV. The final result of screening was determined by the confirmatory test. Statistical analysis Statistical analysis was conducted using SPSS for Windows 16.0. The Chi-square test was applied to evaluate the categorical variants. Odds ratios (OR) and 95% confidence intervals (CI) were calculated for all associations. The logistic regression analysis was used for assessing the influence factors of TTIs, and the independent variables included gender, age, ethnic group, marital status, occupation, education level and donation category. A P value <0.05 was used as the cut-off level for significance. Results Participant characteristics A total of 154 038 blood donors were recorded in the center from 1 January 2008 to 31 December 2015 (Table 1). Among the findings, 44.77% were females and 55.23% were males, and 69.19% were aged 18–34 years, and most were Han Chinese. Additionally, the number of married donors was slightly higher than single donors, and only 0.96% was separated/divorced/widowed. Approximately 58.42% of donors had a college degree or higher level education, and 40.46% had a high school education. Of these, students comprised the largest proportion of donors. The number of first-time donors was higher than repeat donors. Generally, most blood donors were concentrated in the young people group and higher education group. Table 1 The demographic characteristics of blood donors Variable  No. of donors (%)  Gender   Male  85 068 (55.23)   Female  68 970 (44.77)  Age   18–24  40 880 (26.54)   25–29  41 363 (26.85)   30–34  24 342 (15.80)   35–39  21 273 (13.81)   40–44  12 806 (8.31)   45–49  11 100 (7.21)   50–55  2274 (1.48)  Ethnic group   Han Chinese  152 377 (98.92)   Ethnic minorities  1661 (1.08)  Marital status   Single  75 547 (49.04)   Married  77 013 (50.00)   Separated/divorced/widowed  1478 (0.96)  Occupation   Student  60 648 (39.37)   Technology worker  21 214 (13.77)   Farmers  13 320 (8.65)   Businessman  12 848 (8.34)   Health worker  3312 (2.15)   Public officials  6671 (4.33)   Others  36 025 (23.39)  Education level   University education  89 988 (58.42)   Secondary education  62 325 (40.46)   Primary education  1725 (1.12)  Donor status   First-time donor  90 359 (58.66)   Repeat donor  63 679 (41.34)  Variable  No. of donors (%)  Gender   Male  85 068 (55.23)   Female  68 970 (44.77)  Age   18–24  40 880 (26.54)   25–29  41 363 (26.85)   30–34  24 342 (15.80)   35–39  21 273 (13.81)   40–44  12 806 (8.31)   45–49  11 100 (7.21)   50–55  2274 (1.48)  Ethnic group   Han Chinese  152 377 (98.92)   Ethnic minorities  1661 (1.08)  Marital status   Single  75 547 (49.04)   Married  77 013 (50.00)   Separated/divorced/widowed  1478 (0.96)  Occupation   Student  60 648 (39.37)   Technology worker  21 214 (13.77)   Farmers  13 320 (8.65)   Businessman  12 848 (8.34)   Health worker  3312 (2.15)   Public officials  6671 (4.33)   Others  36 025 (23.39)  Education level   University education  89 988 (58.42)   Secondary education  62 325 (40.46)   Primary education  1725 (1.12)  Donor status   First-time donor  90 359 (58.66)   Repeat donor  63 679 (41.34)  Table 1 The demographic characteristics of blood donors Variable  No. of donors (%)  Gender   Male  85 068 (55.23)   Female  68 970 (44.77)  Age   18–24  40 880 (26.54)   25–29  41 363 (26.85)   30–34  24 342 (15.80)   35–39  21 273 (13.81)   40–44  12 806 (8.31)   45–49  11 100 (7.21)   50–55  2274 (1.48)  Ethnic group   Han Chinese  152 377 (98.92)   Ethnic minorities  1661 (1.08)  Marital status   Single  75 547 (49.04)   Married  77 013 (50.00)   Separated/divorced/widowed  1478 (0.96)  Occupation   Student  60 648 (39.37)   Technology worker  21 214 (13.77)   Farmers  13 320 (8.65)   Businessman  12 848 (8.34)   Health worker  3312 (2.15)   Public officials  6671 (4.33)   Others  36 025 (23.39)  Education level   University education  89 988 (58.42)   Secondary education  62 325 (40.46)   Primary education  1725 (1.12)  Donor status   First-time donor  90 359 (58.66)   Repeat donor  63 679 (41.34)  Variable  No. of donors (%)  Gender   Male  85 068 (55.23)   Female  68 970 (44.77)  Age   18–24  40 880 (26.54)   25–29  41 363 (26.85)   30–34  24 342 (15.80)   35–39  21 273 (13.81)   40–44  12 806 (8.31)   45–49  11 100 (7.21)   50–55  2274 (1.48)  Ethnic group   Han Chinese  152 377 (98.92)   Ethnic minorities  1661 (1.08)  Marital status   Single  75 547 (49.04)   Married  77 013 (50.00)   Separated/divorced/widowed  1478 (0.96)  Occupation   Student  60 648 (39.37)   Technology worker  21 214 (13.77)   Farmers  13 320 (8.65)   Businessman  12 848 (8.34)   Health worker  3312 (2.15)   Public officials  6671 (4.33)   Others  36 025 (23.39)  Education level   University education  89 988 (58.42)   Secondary education  62 325 (40.46)   Primary education  1725 (1.12)  Donor status   First-time donor  90 359 (58.66)   Repeat donor  63 679 (41.34)  Prevalence and trend of TTIs among blood donors Compared with 2008, the number of blood donors increased by 33.37% in 2015. It shows that there was an annual increase in blood donation. As revealed in Table 2, positive TTI tests were found in 3245 people, which accounted for 2.11% of all donors. The positive rates of HBsAg, anti-HCV, anti-TP and anti-HIV-1/2 were 0.59, 0.30, 0.99 and 0.23%, respectively. The prevalence of TTIs decreased from 2.39% in 2008 to 1.84% in 2010 but followed a sharp increase to 2.56% in 2011 and then decreased to 1.98% in 2015. In brief, the overall prevalence of TTIs showed a decreasing trend during the past 8 years. Table 2 Positivity rate of transfusion-transmittable infections in blood donors Years  No. of donors  HBsAg  Anti-HCV  Anti-TP  Anti-HIV  Total  Positive rate (%)  95% CIa  Positive rate (%)  95% CI  Positive rate (%)  95% CI  Positive rate (%)  95% CI  Positive rate (%)  95% CI  2008  14 987  0.60  0.48–0.72  0.31  0.22–0.40  1.19  1.02–1.36  0.29  0.20–0.38  2.39  2.14–2.64  2009  16 156  0.61  0.49–0.73  0.15  0.09–0.21  1.08  0.92–1.24  0.33  0.24–0.42  2.17  1.94–2.40  2010  17 581  0.57  0.46–0.68  0.24  0.17–0.31  0.85  0.71–0.99  0.18  0.12–0.24  1.84  1.64–2.04  2011  19 987  0.66  0.55–0.77  0.43  0.34–0.52  1.29  1.13–1.45  0.19  0.13–0.25  2.56  2.34–2.78  2012  20 051  0.67  0.56–0.78  0.40  0.31–0.49  0.96  0.82–1.10  0.25  0.18–0.32  2.28  2.07–2.49  2013  21 232  0.57  0.47–0.67  0.14  0.09–0.19  0.88  0.75–1.01  0.16  0.10–0.21  1.74  1.56–1.92  2014  24 056  0.57  0.47–0.67  0.30  0.23–0.37  0.89  0.77–1.01  0.24  0.18–0.30  1.99  1.81–2.17  2015  19 988  0.50  0.40–0.60  0.42  0.33–0.51  0.84  0.71–0.97  0.23  0.16–0.30  1.98  1.79–2.17  P-valueb    0.38  0.00  0.00  0.01  0.00  Total  154 038  0.59  0.55–0.63  0.30  0.27–0.33  0.99  0.94–1.04  0.23  0.21–0.25  2.11  2.04–2.18  Years  No. of donors  HBsAg  Anti-HCV  Anti-TP  Anti-HIV  Total  Positive rate (%)  95% CIa  Positive rate (%)  95% CI  Positive rate (%)  95% CI  Positive rate (%)  95% CI  Positive rate (%)  95% CI  2008  14 987  0.60  0.48–0.72  0.31  0.22–0.40  1.19  1.02–1.36  0.29  0.20–0.38  2.39  2.14–2.64  2009  16 156  0.61  0.49–0.73  0.15  0.09–0.21  1.08  0.92–1.24  0.33  0.24–0.42  2.17  1.94–2.40  2010  17 581  0.57  0.46–0.68  0.24  0.17–0.31  0.85  0.71–0.99  0.18  0.12–0.24  1.84  1.64–2.04  2011  19 987  0.66  0.55–0.77  0.43  0.34–0.52  1.29  1.13–1.45  0.19  0.13–0.25  2.56  2.34–2.78  2012  20 051  0.67  0.56–0.78  0.40  0.31–0.49  0.96  0.82–1.10  0.25  0.18–0.32  2.28  2.07–2.49  2013  21 232  0.57  0.47–0.67  0.14  0.09–0.19  0.88  0.75–1.01  0.16  0.10–0.21  1.74  1.56–1.92  2014  24 056  0.57  0.47–0.67  0.30  0.23–0.37  0.89  0.77–1.01  0.24  0.18–0.30  1.99  1.81–2.17  2015  19 988  0.50  0.40–0.60  0.42  0.33–0.51  0.84  0.71–0.97  0.23  0.16–0.30  1.98  1.79–2.17  P-valueb    0.38  0.00  0.00  0.01  0.00  Total  154 038  0.59  0.55–0.63  0.30  0.27–0.33  0.99  0.94–1.04  0.23  0.21–0.25  2.11  2.04–2.18  a95% Confidence interval. bChi-square test to examine the change of trend. Table 2 Positivity rate of transfusion-transmittable infections in blood donors Years  No. of donors  HBsAg  Anti-HCV  Anti-TP  Anti-HIV  Total  Positive rate (%)  95% CIa  Positive rate (%)  95% CI  Positive rate (%)  95% CI  Positive rate (%)  95% CI  Positive rate (%)  95% CI  2008  14 987  0.60  0.48–0.72  0.31  0.22–0.40  1.19  1.02–1.36  0.29  0.20–0.38  2.39  2.14–2.64  2009  16 156  0.61  0.49–0.73  0.15  0.09–0.21  1.08  0.92–1.24  0.33  0.24–0.42  2.17  1.94–2.40  2010  17 581  0.57  0.46–0.68  0.24  0.17–0.31  0.85  0.71–0.99  0.18  0.12–0.24  1.84  1.64–2.04  2011  19 987  0.66  0.55–0.77  0.43  0.34–0.52  1.29  1.13–1.45  0.19  0.13–0.25  2.56  2.34–2.78  2012  20 051  0.67  0.56–0.78  0.40  0.31–0.49  0.96  0.82–1.10  0.25  0.18–0.32  2.28  2.07–2.49  2013  21 232  0.57  0.47–0.67  0.14  0.09–0.19  0.88  0.75–1.01  0.16  0.10–0.21  1.74  1.56–1.92  2014  24 056  0.57  0.47–0.67  0.30  0.23–0.37  0.89  0.77–1.01  0.24  0.18–0.30  1.99  1.81–2.17  2015  19 988  0.50  0.40–0.60  0.42  0.33–0.51  0.84  0.71–0.97  0.23  0.16–0.30  1.98  1.79–2.17  P-valueb    0.38  0.00  0.00  0.01  0.00  Total  154 038  0.59  0.55–0.63  0.30  0.27–0.33  0.99  0.94–1.04  0.23  0.21–0.25  2.11  2.04–2.18  Years  No. of donors  HBsAg  Anti-HCV  Anti-TP  Anti-HIV  Total  Positive rate (%)  95% CIa  Positive rate (%)  95% CI  Positive rate (%)  95% CI  Positive rate (%)  95% CI  Positive rate (%)  95% CI  2008  14 987  0.60  0.48–0.72  0.31  0.22–0.40  1.19  1.02–1.36  0.29  0.20–0.38  2.39  2.14–2.64  2009  16 156  0.61  0.49–0.73  0.15  0.09–0.21  1.08  0.92–1.24  0.33  0.24–0.42  2.17  1.94–2.40  2010  17 581  0.57  0.46–0.68  0.24  0.17–0.31  0.85  0.71–0.99  0.18  0.12–0.24  1.84  1.64–2.04  2011  19 987  0.66  0.55–0.77  0.43  0.34–0.52  1.29  1.13–1.45  0.19  0.13–0.25  2.56  2.34–2.78  2012  20 051  0.67  0.56–0.78  0.40  0.31–0.49  0.96  0.82–1.10  0.25  0.18–0.32  2.28  2.07–2.49  2013  21 232  0.57  0.47–0.67  0.14  0.09–0.19  0.88  0.75–1.01  0.16  0.10–0.21  1.74  1.56–1.92  2014  24 056  0.57  0.47–0.67  0.30  0.23–0.37  0.89  0.77–1.01  0.24  0.18–0.30  1.99  1.81–2.17  2015  19 988  0.50  0.40–0.60  0.42  0.33–0.51  0.84  0.71–0.97  0.23  0.16–0.30  1.98  1.79–2.17  P-valueb    0.38  0.00  0.00  0.01  0.00  Total  154 038  0.59  0.55–0.63  0.30  0.27–0.33  0.99  0.94–1.04  0.23  0.21–0.25  2.11  2.04–2.18  a95% Confidence interval. bChi-square test to examine the change of trend. Moreover, our results show that the number of syphilis infection cases was the highest among all TTIs. The highest positive rate of syphilis was 1.29% in 2011 and the lowest was 0.84% in 2015 (P < 0.01), and the number of positive syphilis cases showed a fluctuating trend, which was similar to the overall prevalence. Additionally, both HCV and HIV prevalence revealed a general trend of fluctuations. The positive rate of HCV ranged from 0.14 to 0.43% (P < 0.01), and the positive rate of HIV varied in a range between 0.16 and 0.33% (P < 0.01). However, in comparing syphilis, HCV and HIV, the trends differed. In TTIs, the positive cases of HBV varied between 0.50 and 0.67% (P = 0.38). HBV prevalence revealed a steady trend and barely changed in this period. The demographic characteristics of positive TTIs The characteristics of the positive TTI crowd were classified and analyzed statistically in Table 3. Our results showed that the positive rate of females (2.23%) was higher than that of males (2.01%) in overall TTI prevalence. The percentage of female syphilis cases was much higher than that of males, and the difference was significant (P < 0.01). However, HBV, HCV and HIV infections did not significantly differ between genders (P > 0.05). The HCV and HIV infection cases were more distributed in the 18–24 age group (0.57 and 0.42%, respectively), and HBV and syphilis infections were more distributed in the 40–44 (0.75%) and 45–55 age groups (2.09%), respectively. The higher TTIs infection rates were concentrated in the younger and higher aged groups. Although the separated/divorced/widowed group accounted for only 0.96% of all donors, their positive rate of TTI infection was the highest, reaching 6.02%. Specifically, the positive rate of syphilis reached 3.59% in this group, and the rate was much higher than the single (0.53%) and married (1.38%) groups. Students were accounts for 39.37% in total. However, the positive infection rate of students was only 0.84%, and it was the lowest value in the entire list. Furthermore, the highest positive rate of HBV and syphilis was in the farmer group (1.67 and 2.73%, respectively), and the highest rate of HCV and HIV infections was in the public officials group (0.69 and 0.61%, respectively). Most donors were educated beyond the primary level, but the highest prevalence of TTIs occurred in donors with only a primary education. Both donor number and TTI positive rate in first-time donors were higher than repeat donors. The results lead us to the conclusion that the TTI with the highest prevalence was syphilis among blood donors in Southwest China between 2008 and 2015, and the highest positive rate of TTIs occurred in females, aged 45–55, separated/divorced/widowed people, farmers, primary education level and first-time donors. Table 3 Positivity rate of TTIs by demographic characteristics Variable  No. of donors  HBsAg  Anti-HCV  Anti-TP  Anti-HIV  Total  Positive rate (%)  95% CIa  Positive rate (%)  95% CI  Positive rate (%)  95% CI  Positive rate  95% CI  Positive rate  95% CI  Gender   Male  85 068  0.59  0.54–0.64  0.32  0.28–0.36  0.87  0.81–0.93  0.22  0.19–0.25  2.01  1.91–2.11   Female  68 970  0.59  0.53–0.65  0.27  0.23–0.31  1.13  1.05–1.21  0.24  0.20–0.28  2.23  2.12–2.34   P-valueb    0.97  0.07  0.00  0.50  0.00  Age   18–24  40 880  0.69  0.61–0.77  0.57  0.50–0.64  0.50  0.43–0.57  0.42  0.36–0.48  2.19  2.05–2.33   25–29  41 363  0.44  0.38–0.50  0.20  0.16–0.24  0.62  0.54–0.70  0.17  0.13–0.21  1.42  1.30–1.54   30–34  24 342  0.53  0.44–0.62  0.17  0.12–0.22  0.97  0.85–1.09  0.15  0.10–0.20  1.82  1.65–1.99   35–39  21 273  0.62  0.51–0.73  0.18  0.12–0.24  1.34  1.18–1.50  0.14  0.09–0.19  2.28  2.08–2.48   40–44  12 806  0.75  0.60–0.90  0.26  0.17–0.35  2.01  1.77–2.25  0.16  0.09–0.23  3.17  2.86–3.48   45–55  13 374  0.69  0.55–0.83  0.27  0.18–0.36  2.09  1.85–2.33  0.17  0.10–0.24  3.22  2.92–3.52   P-value    0.00  0.00  0.00  0.00  0.00  Marital status   Single  75 547  0.57  0.52–0.62  0.41  0.36–0.46  0.53  0.48–0.58  0.30  0.26–0.34  1.81  1.71–1.91   Married  77 013  0.59  0.54–0.64  0.19  0.16–0.22  1.38  1.30–1.46  0.15  0.12–0.18  2.32  2.21–2.43   Separated/divorced/widowed  1478  1.42  0.81–2.03  0.47  0.12–0.82  3.59  2.63–4.55  0.54  0.17–0.91  6.02  4.78–7.26   P-value    0.00  0.00  0.00  0.00  0.00  Occupation   Student  60 648  0.29  0.25–0.33  0.19  0.16–0.22  0.26  0.22–0.30  0.11  0.08–0.14  0.84  0.77–0.91   Technology worker  21 214  0.86  0.74–0.98  0.43  0.34–0.52  1.95  1.76–2.14  0.29  0.22–0.36  3.53  3.28–3.78   Farmers  13 320  1.67  1.45–1.89  0.61  0.48–0.74  2.73  2.45–3.01  0.48  0.36–0.60  5.49  5.09–5.89   Businessman  12 848  0.93  0.76–1.10  0.36  0.26–0.46  2.05  1.80–2.30  0.30  0.21–0.39  3.64  3.31–3.97   Health worker  3312  0.21  0.05–0.37  0.21  0.05–0.37  0.36  0.16–0.56  0.21  0.05–0.37  1.00  0.66–1.34   Public officials  6671  1.09  0.84–1.34  0.69  0.49–0.89  1.50  1.21–1.79  0.61  0.42–0.80  3.90  3.43–4.37   Others  36 025  0.37  0.31–0.43  0.22  0.17–0.27  0.58  0.50–0.66  0.20  0.15–0.25  1.37  1.25–1.49   P-value    0.00  0.00  0.00  0.00  0.00  Education level   Primary or less  1725  2.03  1.36–2.70  0.93  0.48–1.38  3.94  3.00–4.88  0.70  0.30–1.08  7.59  6.27–8.89   Secondary  62 325  0.80  0.73–0.87  0.39  0.34–0.44  1.72  1.62–1.82  0.29  0.24–0.32  3.21  3.05–3.33   University or above  89 988  0.42  0.29–0.55  0.23  0.20–0.43  0.41  0.37–0.45  0.18  0.15–0.21  1.23  1.16–1.30   P-value    0.00  0.00  0.00  0.00  0.00  Donor category   First time  90 359  0.92  0.86–0.98  0.42  0.38–0.46  1.59  1.51–1.67  0.30  0.26–0.34  3.22  3.10–3.34   Repeated  63 679  0.13  0.10–0.16  0.13  0.10–0.16  0.13  0.10–0.16  0.13  0.10–0.16  0.52  0.46–0.58   P-value    0.00  0.00  0.00  0.00  0.00  Total  154 038  0.59  0.55–0.63  0.30  0.27–0.33  0.99  0.94–1.04  0.23  0.21–0.25  2.11  2.04–2.18  Variable  No. of donors  HBsAg  Anti-HCV  Anti-TP  Anti-HIV  Total  Positive rate (%)  95% CIa  Positive rate (%)  95% CI  Positive rate (%)  95% CI  Positive rate  95% CI  Positive rate  95% CI  Gender   Male  85 068  0.59  0.54–0.64  0.32  0.28–0.36  0.87  0.81–0.93  0.22  0.19–0.25  2.01  1.91–2.11   Female  68 970  0.59  0.53–0.65  0.27  0.23–0.31  1.13  1.05–1.21  0.24  0.20–0.28  2.23  2.12–2.34   P-valueb    0.97  0.07  0.00  0.50  0.00  Age   18–24  40 880  0.69  0.61–0.77  0.57  0.50–0.64  0.50  0.43–0.57  0.42  0.36–0.48  2.19  2.05–2.33   25–29  41 363  0.44  0.38–0.50  0.20  0.16–0.24  0.62  0.54–0.70  0.17  0.13–0.21  1.42  1.30–1.54   30–34  24 342  0.53  0.44–0.62  0.17  0.12–0.22  0.97  0.85–1.09  0.15  0.10–0.20  1.82  1.65–1.99   35–39  21 273  0.62  0.51–0.73  0.18  0.12–0.24  1.34  1.18–1.50  0.14  0.09–0.19  2.28  2.08–2.48   40–44  12 806  0.75  0.60–0.90  0.26  0.17–0.35  2.01  1.77–2.25  0.16  0.09–0.23  3.17  2.86–3.48   45–55  13 374  0.69  0.55–0.83  0.27  0.18–0.36  2.09  1.85–2.33  0.17  0.10–0.24  3.22  2.92–3.52   P-value    0.00  0.00  0.00  0.00  0.00  Marital status   Single  75 547  0.57  0.52–0.62  0.41  0.36–0.46  0.53  0.48–0.58  0.30  0.26–0.34  1.81  1.71–1.91   Married  77 013  0.59  0.54–0.64  0.19  0.16–0.22  1.38  1.30–1.46  0.15  0.12–0.18  2.32  2.21–2.43   Separated/divorced/widowed  1478  1.42  0.81–2.03  0.47  0.12–0.82  3.59  2.63–4.55  0.54  0.17–0.91  6.02  4.78–7.26   P-value    0.00  0.00  0.00  0.00  0.00  Occupation   Student  60 648  0.29  0.25–0.33  0.19  0.16–0.22  0.26  0.22–0.30  0.11  0.08–0.14  0.84  0.77–0.91   Technology worker  21 214  0.86  0.74–0.98  0.43  0.34–0.52  1.95  1.76–2.14  0.29  0.22–0.36  3.53  3.28–3.78   Farmers  13 320  1.67  1.45–1.89  0.61  0.48–0.74  2.73  2.45–3.01  0.48  0.36–0.60  5.49  5.09–5.89   Businessman  12 848  0.93  0.76–1.10  0.36  0.26–0.46  2.05  1.80–2.30  0.30  0.21–0.39  3.64  3.31–3.97   Health worker  3312  0.21  0.05–0.37  0.21  0.05–0.37  0.36  0.16–0.56  0.21  0.05–0.37  1.00  0.66–1.34   Public officials  6671  1.09  0.84–1.34  0.69  0.49–0.89  1.50  1.21–1.79  0.61  0.42–0.80  3.90  3.43–4.37   Others  36 025  0.37  0.31–0.43  0.22  0.17–0.27  0.58  0.50–0.66  0.20  0.15–0.25  1.37  1.25–1.49   P-value    0.00  0.00  0.00  0.00  0.00  Education level   Primary or less  1725  2.03  1.36–2.70  0.93  0.48–1.38  3.94  3.00–4.88  0.70  0.30–1.08  7.59  6.27–8.89   Secondary  62 325  0.80  0.73–0.87  0.39  0.34–0.44  1.72  1.62–1.82  0.29  0.24–0.32  3.21  3.05–3.33   University or above  89 988  0.42  0.29–0.55  0.23  0.20–0.43  0.41  0.37–0.45  0.18  0.15–0.21  1.23  1.16–1.30   P-value    0.00  0.00  0.00  0.00  0.00  Donor category   First time  90 359  0.92  0.86–0.98  0.42  0.38–0.46  1.59  1.51–1.67  0.30  0.26–0.34  3.22  3.10–3.34   Repeated  63 679  0.13  0.10–0.16  0.13  0.10–0.16  0.13  0.10–0.16  0.13  0.10–0.16  0.52  0.46–0.58   P-value    0.00  0.00  0.00  0.00  0.00  Total  154 038  0.59  0.55–0.63  0.30  0.27–0.33  0.99  0.94–1.04  0.23  0.21–0.25  2.11  2.04–2.18  a95% Confidence interval. bChi-square trend test to test statistical difference in the distribution with each group. Table 3 Positivity rate of TTIs by demographic characteristics Variable  No. of donors  HBsAg  Anti-HCV  Anti-TP  Anti-HIV  Total  Positive rate (%)  95% CIa  Positive rate (%)  95% CI  Positive rate (%)  95% CI  Positive rate  95% CI  Positive rate  95% CI  Gender   Male  85 068  0.59  0.54–0.64  0.32  0.28–0.36  0.87  0.81–0.93  0.22  0.19–0.25  2.01  1.91–2.11   Female  68 970  0.59  0.53–0.65  0.27  0.23–0.31  1.13  1.05–1.21  0.24  0.20–0.28  2.23  2.12–2.34   P-valueb    0.97  0.07  0.00  0.50  0.00  Age   18–24  40 880  0.69  0.61–0.77  0.57  0.50–0.64  0.50  0.43–0.57  0.42  0.36–0.48  2.19  2.05–2.33   25–29  41 363  0.44  0.38–0.50  0.20  0.16–0.24  0.62  0.54–0.70  0.17  0.13–0.21  1.42  1.30–1.54   30–34  24 342  0.53  0.44–0.62  0.17  0.12–0.22  0.97  0.85–1.09  0.15  0.10–0.20  1.82  1.65–1.99   35–39  21 273  0.62  0.51–0.73  0.18  0.12–0.24  1.34  1.18–1.50  0.14  0.09–0.19  2.28  2.08–2.48   40–44  12 806  0.75  0.60–0.90  0.26  0.17–0.35  2.01  1.77–2.25  0.16  0.09–0.23  3.17  2.86–3.48   45–55  13 374  0.69  0.55–0.83  0.27  0.18–0.36  2.09  1.85–2.33  0.17  0.10–0.24  3.22  2.92–3.52   P-value    0.00  0.00  0.00  0.00  0.00  Marital status   Single  75 547  0.57  0.52–0.62  0.41  0.36–0.46  0.53  0.48–0.58  0.30  0.26–0.34  1.81  1.71–1.91   Married  77 013  0.59  0.54–0.64  0.19  0.16–0.22  1.38  1.30–1.46  0.15  0.12–0.18  2.32  2.21–2.43   Separated/divorced/widowed  1478  1.42  0.81–2.03  0.47  0.12–0.82  3.59  2.63–4.55  0.54  0.17–0.91  6.02  4.78–7.26   P-value    0.00  0.00  0.00  0.00  0.00  Occupation   Student  60 648  0.29  0.25–0.33  0.19  0.16–0.22  0.26  0.22–0.30  0.11  0.08–0.14  0.84  0.77–0.91   Technology worker  21 214  0.86  0.74–0.98  0.43  0.34–0.52  1.95  1.76–2.14  0.29  0.22–0.36  3.53  3.28–3.78   Farmers  13 320  1.67  1.45–1.89  0.61  0.48–0.74  2.73  2.45–3.01  0.48  0.36–0.60  5.49  5.09–5.89   Businessman  12 848  0.93  0.76–1.10  0.36  0.26–0.46  2.05  1.80–2.30  0.30  0.21–0.39  3.64  3.31–3.97   Health worker  3312  0.21  0.05–0.37  0.21  0.05–0.37  0.36  0.16–0.56  0.21  0.05–0.37  1.00  0.66–1.34   Public officials  6671  1.09  0.84–1.34  0.69  0.49–0.89  1.50  1.21–1.79  0.61  0.42–0.80  3.90  3.43–4.37   Others  36 025  0.37  0.31–0.43  0.22  0.17–0.27  0.58  0.50–0.66  0.20  0.15–0.25  1.37  1.25–1.49   P-value    0.00  0.00  0.00  0.00  0.00  Education level   Primary or less  1725  2.03  1.36–2.70  0.93  0.48–1.38  3.94  3.00–4.88  0.70  0.30–1.08  7.59  6.27–8.89   Secondary  62 325  0.80  0.73–0.87  0.39  0.34–0.44  1.72  1.62–1.82  0.29  0.24–0.32  3.21  3.05–3.33   University or above  89 988  0.42  0.29–0.55  0.23  0.20–0.43  0.41  0.37–0.45  0.18  0.15–0.21  1.23  1.16–1.30   P-value    0.00  0.00  0.00  0.00  0.00  Donor category   First time  90 359  0.92  0.86–0.98  0.42  0.38–0.46  1.59  1.51–1.67  0.30  0.26–0.34  3.22  3.10–3.34   Repeated  63 679  0.13  0.10–0.16  0.13  0.10–0.16  0.13  0.10–0.16  0.13  0.10–0.16  0.52  0.46–0.58   P-value    0.00  0.00  0.00  0.00  0.00  Total  154 038  0.59  0.55–0.63  0.30  0.27–0.33  0.99  0.94–1.04  0.23  0.21–0.25  2.11  2.04–2.18  Variable  No. of donors  HBsAg  Anti-HCV  Anti-TP  Anti-HIV  Total  Positive rate (%)  95% CIa  Positive rate (%)  95% CI  Positive rate (%)  95% CI  Positive rate  95% CI  Positive rate  95% CI  Gender   Male  85 068  0.59  0.54–0.64  0.32  0.28–0.36  0.87  0.81–0.93  0.22  0.19–0.25  2.01  1.91–2.11   Female  68 970  0.59  0.53–0.65  0.27  0.23–0.31  1.13  1.05–1.21  0.24  0.20–0.28  2.23  2.12–2.34   P-valueb    0.97  0.07  0.00  0.50  0.00  Age   18–24  40 880  0.69  0.61–0.77  0.57  0.50–0.64  0.50  0.43–0.57  0.42  0.36–0.48  2.19  2.05–2.33   25–29  41 363  0.44  0.38–0.50  0.20  0.16–0.24  0.62  0.54–0.70  0.17  0.13–0.21  1.42  1.30–1.54   30–34  24 342  0.53  0.44–0.62  0.17  0.12–0.22  0.97  0.85–1.09  0.15  0.10–0.20  1.82  1.65–1.99   35–39  21 273  0.62  0.51–0.73  0.18  0.12–0.24  1.34  1.18–1.50  0.14  0.09–0.19  2.28  2.08–2.48   40–44  12 806  0.75  0.60–0.90  0.26  0.17–0.35  2.01  1.77–2.25  0.16  0.09–0.23  3.17  2.86–3.48   45–55  13 374  0.69  0.55–0.83  0.27  0.18–0.36  2.09  1.85–2.33  0.17  0.10–0.24  3.22  2.92–3.52   P-value    0.00  0.00  0.00  0.00  0.00  Marital status   Single  75 547  0.57  0.52–0.62  0.41  0.36–0.46  0.53  0.48–0.58  0.30  0.26–0.34  1.81  1.71–1.91   Married  77 013  0.59  0.54–0.64  0.19  0.16–0.22  1.38  1.30–1.46  0.15  0.12–0.18  2.32  2.21–2.43   Separated/divorced/widowed  1478  1.42  0.81–2.03  0.47  0.12–0.82  3.59  2.63–4.55  0.54  0.17–0.91  6.02  4.78–7.26   P-value    0.00  0.00  0.00  0.00  0.00  Occupation   Student  60 648  0.29  0.25–0.33  0.19  0.16–0.22  0.26  0.22–0.30  0.11  0.08–0.14  0.84  0.77–0.91   Technology worker  21 214  0.86  0.74–0.98  0.43  0.34–0.52  1.95  1.76–2.14  0.29  0.22–0.36  3.53  3.28–3.78   Farmers  13 320  1.67  1.45–1.89  0.61  0.48–0.74  2.73  2.45–3.01  0.48  0.36–0.60  5.49  5.09–5.89   Businessman  12 848  0.93  0.76–1.10  0.36  0.26–0.46  2.05  1.80–2.30  0.30  0.21–0.39  3.64  3.31–3.97   Health worker  3312  0.21  0.05–0.37  0.21  0.05–0.37  0.36  0.16–0.56  0.21  0.05–0.37  1.00  0.66–1.34   Public officials  6671  1.09  0.84–1.34  0.69  0.49–0.89  1.50  1.21–1.79  0.61  0.42–0.80  3.90  3.43–4.37   Others  36 025  0.37  0.31–0.43  0.22  0.17–0.27  0.58  0.50–0.66  0.20  0.15–0.25  1.37  1.25–1.49   P-value    0.00  0.00  0.00  0.00  0.00  Education level   Primary or less  1725  2.03  1.36–2.70  0.93  0.48–1.38  3.94  3.00–4.88  0.70  0.30–1.08  7.59  6.27–8.89   Secondary  62 325  0.80  0.73–0.87  0.39  0.34–0.44  1.72  1.62–1.82  0.29  0.24–0.32  3.21  3.05–3.33   University or above  89 988  0.42  0.29–0.55  0.23  0.20–0.43  0.41  0.37–0.45  0.18  0.15–0.21  1.23  1.16–1.30   P-value    0.00  0.00  0.00  0.00  0.00  Donor category   First time  90 359  0.92  0.86–0.98  0.42  0.38–0.46  1.59  1.51–1.67  0.30  0.26–0.34  3.22  3.10–3.34   Repeated  63 679  0.13  0.10–0.16  0.13  0.10–0.16  0.13  0.10–0.16  0.13  0.10–0.16  0.52  0.46–0.58   P-value    0.00  0.00  0.00  0.00  0.00  Total  154 038  0.59  0.55–0.63  0.30  0.27–0.33  0.99  0.94–1.04  0.23  0.21–0.25  2.11  2.04–2.18  a95% Confidence interval. bChi-square trend test to test statistical difference in the distribution with each group. Influential factors of TTIs To define the influencing factors of TTIs, a logistic regression analysis model was established (Table 4). In this model, gender, age, marital status, occupation, education level and donor category were included in the analysis, and the reference group of these variables was male, age 18–24, single, student, university level or above and first-time donors. The results show that the positive rate of transfusion-transmitted infectious diseases was independently associated with age, occupation and donor category. Table 4 Influential factors of transfusion-transmittable infectionsa Variable  P-valueb  Odds ratio  95% CIc  Age  0.00  1.14  1.11–1.16  Occupation  0.00  0.68  0.60–0.77  Donor category  0.00  0.14  0.13–0.16  Variable  P-valueb  Odds ratio  95% CIc  Age  0.00  1.14  1.11–1.16  Occupation  0.00  0.68  0.60–0.77  Donor category  0.00  0.14  0.13–0.16  aIn logistic regression analysis, the reference group of these variables was male, age 18–24, single, student, university level or above and first-time donors. bChi-square trend test to test the statistical difference in each group. c95% Confidence interval. Table 4 Influential factors of transfusion-transmittable infectionsa Variable  P-valueb  Odds ratio  95% CIc  Age  0.00  1.14  1.11–1.16  Occupation  0.00  0.68  0.60–0.77  Donor category  0.00  0.14  0.13–0.16  Variable  P-valueb  Odds ratio  95% CIc  Age  0.00  1.14  1.11–1.16  Occupation  0.00  0.68  0.60–0.77  Donor category  0.00  0.14  0.13–0.16  aIn logistic regression analysis, the reference group of these variables was male, age 18–24, single, student, university level or above and first-time donors. bChi-square trend test to test the statistical difference in each group. c95% Confidence interval. Discussion Blood transfusion is a life-saving measure. However, transfusion is an efficient mode of transmission for blood borne infections. Therefore, TTI infection assessment has great significance for clinical transfusion safety.15 Our research shows that the overall prevalence of TTIs was slightly lower in Southwest China, but the syphilis infection rate was significantly higher than that in Nanjing (0.36%), Guangzhou (0.42%), Liaoning (0.60%) and Yancheng (0.70%).16 The positive rate of syphilis was the highest among TTIs, and the rate was 0.99%, which was higher than that of HBV (0.59%), HCV (0.30%) and HIV (0.23). Additionally, females accounted for a higher percentage than males among syphilis cases. The China CDC has reported that the number of recorded cases of syphilis was 40 849 individuals at the end of 2015, and it increased by 5% compared with the last year. Notably, the infection number of females was higher than males, and the ratio was 1:0.9.17 The number of syphilis infections in the general population showed a sharp increase in recent years, and the gender differences have been presented in the data. Both the blood donors and general population with syphilis demonstrated a high prevalence trend, and the female infection rate was higher than that in males. The results may be associated with many factors, such as economic conditions and cultural and social environments. In Southwest China, the local economy is less developed than in the eastern region because of certain limitations, such as economic and public traffic. Therefore, a large amount of the labor force are in the east or other developed economic regions each year, and many women remain in the country to care for the family. Long-term separation may lead to unstable family surroundings or un-marriage sexual behavior was increased, which is accompanied by having various sexual partners, which may be associated with sexual transmission was increased.18 Additionally, sexual transmission between spouses has also increased, and this situation may cause an increase in females with syphilis infection.17 Moreover, it has been reported that the occupation with the highest syphilis rate was the farmers group among blood donors.18,19 This is the same as our results, and the highest positive rate of TTIs was in the farmers group in our study. The farmers group is a special population, and most of them live in rural areas where the culture and information is relatively behind that in the city. Thus, the population lacks awareness of TTI prevention and control. Additionally, the sexual attitudes of the population changed from closed to open, and non-marital sexual behavior increased in recent years. Thus, all these factors increased the infection risk in farmers.20,21 To reduce the prevalence of HBV infection, the central government promoted the hepatitis B vaccination in 1992 for the general population, and all newborns have been given this vaccine for free since 2005.22 Although these measures effectively reduced the prevalence of HBV, there are ~100 million infections in China.23,24 In this study, the HBV infection rate was significantly lower than in the general population (7.2%) because donations were canceled if there was a positive HBsAg in pre-donation testing. Pre-donation testing could exclude HBV infected and co-infected donors. Unfortunately, the excluded donors were not analyzed in our study because their information was too difficult to collect. This may be the reason why the results were too low, and there are no co-infected donors in our study. However, the HBV infection analysis of blood donors has a great significance for monitoring the blood donation security. A total of 3.2% of the general population has HCV in China, and ~150 million people are infected with it in the world.7 HCV was eliminated recently following a large-scale prevention and control policy in China. The positive rate of HCV was 12.87% in blood donors before 1998 and significantly decreased to 1.71% after 1998.7,25 In our study, the overall prevalence of HCV was only 0.30% in Southwest China, and the positive rate of HCV varied between 0.14 and 0.43% from 2008 to 2015. The rate was lower than that in other Chinese regions.19,26 HCV infection has a low prevalence among blood donors in Southwest China. Additionally, the number of HCV-infected males was more than that of females, but there were no significant differences between genders. This gender distribution was the same as the previous reports from Xi’an,26 Guangzhou and Nanjing,16 and different from Shiyan.18 HIV is a serious infection that endangers public health in the world. At the end of 2015, a total of 577 423 HIV/AIDS cases were reported, and the number of deaths was 182 882 in China. The number of infections in males was more than females, and sexual transmission caused the largest proportion of HIV infection.17 In this study, the HIV infection rate was 0.23% among blood donors in Southwest China. The value was higher than that in Xi’an,26 Liaoning, Guangzhou16 and Shiyan18 and lower than that in the blood donors in Western China.19 The findings were consistent with the CDC report, and HIV infection occurs mainly through sexual transmission in blood donors. However, there were no significant differences between genders. Moreover, the CDC has reported that the number of people <15 years old has increased annually in the general population,17 and our study shows that the highest infectious burden occurred in the 18–24-year group. Those who are becoming infected with HIV are increasingly younger. With improving the HIV Monitoring Network, the effective detection and management of the high-risk population is conducive to HIV/AIDS prevention.27 However, the high prevalence of HIV is still a serious threat for blood transfusion safety in China. Generally, TTIs have a high prevalence in China compared with other countries, and more efforts are needed to ensure blood safety in the long term.9,28 The government should further strengthen the spread of knowledge and information of TTI prevention, especially in rural regions, to improve the awareness of disease prevention in the general population.20,21 Additionally, intervention management of the high-risk population should be further increased to achieve better disease control. The standard blood collection and screening process needs further improvement for guaranteeing blood safety. In standard Chinese procedures, TTI detection was occurred using ELISA, and the ‘window period’ of this method is between 2 weeks and 3 months. Given that testing is confined to serologic testing, there remains risk of transmission of incident TTIs in the pre-seroconversion window period.29,30 Therefore, many countries have adopted nucleic acid testing (NAT) for screening because NAT has the ability to shorten the ‘window period’ for reducing TTI residual risks.9,28 At present, NAT was only used at the larger blood centers in China because it was limited by high cost and people with advanced training. To improve the application of NAT, the Chinese government has formulated an effective policy for helping all blood centers to complete the detection system. These measures would help to reduce the prevalence of TTIs and ensure the safety of the blood supply in the long term. Acknowledgements The authors gratefully acknowledge all the staff members of the blood center for their support during data collection. References 1 Seitz R, Heiden M. Quality and safety in blood supply in 2010. Transfus Med Hemother  2010; 37( 3): 112– 7. Google Scholar CrossRef Search ADS PubMed  2 Luban NL. Transfusion safety: where are we today? Ann NY Acad Sci  2005; 1054: 325– 41. Google Scholar CrossRef Search ADS PubMed  3 Bönig H, Schmidt M, Hourfar K et al.  . Sufficient blood, safe blood: can we have both? BMC Med  2012; 10: 29. Google Scholar CrossRef Search ADS PubMed  4 Ministry of Health of China, World Health Organization, Joint United Nations Programme on HIV/AIDS. 2005 Update on the HIV/AIDS Epidemic and Response in China. Beijing: Ministry of Health 2006. 5 Ministry of Health of China, World Health Organization, Joint United Nations Programme on HIV/AIDS. 2014 Update on the HIV/AIDS Epidemic and Response in China. Beijing: Ministry of Health 2015. 6 Guo XC, Wu YQ. A review: progress of prevention and control of viral hepatitis in China. Biomed Environ Sci  1999; 12( 3): 227– 32. Google Scholar PubMed  7 Gao XF, Cui Q, Shi X et al.  . Prevalence and trend of hepatitis C virus infection among blood donors in Chinese mainland: a systematic review and metamorphosis. BMC Infect Dis  2012; 11: 88. Google Scholar CrossRef Search ADS   8 Seo DH, Whang DH, Song EY et al.  . Occult hepatitis B virus infection and blood transfusion. World J Hepatol  2015; 7( 3): 600– 6. Google Scholar CrossRef Search ADS PubMed  9 Kim MJ, Park Q, Min HK et al.  . Residual risk of transfusion-transmitted infection with human immunodeficiency virus, hepatitis C virus, and hepatitis B virus in Korea from 2000 through 2010. BMC Infect Dis  2012; 12: 160. Google Scholar CrossRef Search ADS PubMed  10 Chen ZQ, Zhang GC, Gong XD et al.  . Syphilis in China: results of a national surveillance programme. Lancet  2007; 369( 9556): 132– 8. Google Scholar CrossRef Search ADS PubMed  11 Liu J, Huang Y, Wang JX et al.  . The increasing prevalence of serologic markers for syphilis among Chinese blood donors in 2008 through 2010 during a syphilis epidemic. Transfusion  2012; 52( 8): 1741– 9. Google Scholar CrossRef Search ADS PubMed  12 Erwin K. The circulatory system: blood procurement, AIDS, and the social body in China. Med Anthropol Q  2006; 20( 2): 139– 59. Google Scholar CrossRef Search ADS PubMed  13 Adams V, Erwin K, Le PV. Public health works: blood donation in urban China. Soc Sci Med  2009; 68( 3): 410– 8. Google Scholar CrossRef Search ADS PubMed  14 Shan H, Wang JX, Ren FR et al.  . Blood banking in China. Lancet  2002; 360( 9347): 1770– 5. Google Scholar CrossRef Search ADS PubMed  15 Glynn SA, Busch MP, Schreiber GB et al.  . Effect of a national disaster on blood supply and safety: the September 11 experience. J Am Med Assoc  2003; 289( 17): 2246– 53. Google Scholar CrossRef Search ADS   16 Li C, Xiao X, Yin H et al.  . Prevalence and prevalence trends of transfusion transmissible infections among blood donors at four Chinese regional blood centers between 2000 and 2010. J Transl Med  2012; 10: 176. Google Scholar CrossRef Search ADS PubMed  17 National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention. Update on the AIDS/STD epidemic in China and main response in control and prevention in December, 2015. Chin J AIDS STD  2016; 22( 2): 69. 18 Yang SG, Jiao DM, Liu CJ et al.  . Serioprevalence of human immunodeficiency virus, hepatitis B and C viruses, and Treponema pallidum infections among blood donors at Shiyan, Central China. BMC Infect Dis  2016; 16: 531. Google Scholar CrossRef Search ADS PubMed  19 Song Y, Bian Y, Petzold M et al.  . Prevalence and trend of major transfusion-transmissible infections among blood donors in Western China, 2005 through 2010. PLOS One  2014; 9( 4): e94528. Google Scholar CrossRef Search ADS PubMed  20 Dong R, Qiao X, Jia W et al.  . HIV, HCV, and HBV co-infections in a rural area of Shanxi province with a history of commercial blood donation. Biomed Environ Sci  2011; 24( 3): 207– 13. Google Scholar PubMed  21 Zaller N, Nelson KE, Ness P et al.  . Demographic characteristics and risks for transfusion-transmissible infection among blood donors in Xinjiang autonomous region, People’s Republic of China. Transfusion  2006; 46( 2): 265– 71. Google Scholar CrossRef Search ADS PubMed  22 Liang XF, Bi SL, Yang WZ et al.  . Evaluation of the impact of hepatitis B vaccination among children born during 1992–2005 in China. J Infect Dis  2009; 200( 1): 39– 47. Google Scholar CrossRef Search ADS PubMed  23 Liang XF, Bi SL, Yang WZ et al.  . Epidemiological serosurvey of hepatitis B in China declining HBV prevalence due to hepatitis B vaccination. Vaccine  2009; 27( 47): 6550– 7. Google Scholar CrossRef Search ADS PubMed  24 Luo Z, Li L, Ruan B. Impact of the implementation of a vaccination strategy on hepatitis B virus infections in China over a 20-year period. Int J Infect Dis  2012; 16( 2): e82– 8. Google Scholar CrossRef Search ADS PubMed  25 Fu Y, Wang Y, Xia W et al.  . New trends of HCV infection in China revealed by genetic analysis of viral sequences determined from first-time volunteer blood donors. J Viral Hepat  2011; 18( 1): 42– 52. Google Scholar CrossRef Search ADS PubMed  26 Ji ZH, Li CY, Lv YG et al.  . The prevalence and trends of transfusion-transmissible infectious pathogens among first-time, voluntary blood donors in Xi’an, China between 1999 and 2009. Int J Infect Dis  2013; 17( 4): 259– 62. Google Scholar CrossRef Search ADS   27 Wang LD. Overview of the HIV/AIDS epidemic, scientific research and government responses in China. AIDS  2007; 21( Suppl 8): S3– 7. Google Scholar CrossRef Search ADS PubMed  28 Tani Y, Aso H, Matsukura H et al.  . Significant background rates of HBV and HCV infections in patients and risks of blood transfusion from donors with low anti-HBc titres or high anti-HBc titres with high anti-HBs titres in Japan: a prospective, individual NAT study of transfusion-transmitted HBV, HCV and HIV infections. Vox Sang  2012; 102( 4): 285– 93. Google Scholar CrossRef Search ADS PubMed  29 Bruhn R, Lelie N, Busch M et al.  . Relative efficacy of nucleic acid amplification testing and serologic screening in preventing hepatitis C virus transmission risk in seven international regions. Transfusion  2015; 55( 6): 1195– 205. Google Scholar CrossRef Search ADS PubMed  30 De Souza MS, Phanuphak N, Pinyakorn S et al.  . Impact of nucleic acid testing relative to antigen/antibody combination immunoassay on the detection of acute HIV infection. AIDS  2015; 29( 7): 793– 800. Google Scholar CrossRef Search ADS PubMed  © The Author(s) 2018. Published by Oxford University Press on behalf of Faculty of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com

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Journal of Public HealthOxford University Press

Published: Jan 17, 2018

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