Meta-analysis of adherence to highly active antiretroviral therapy in patients with HIV infection in China

ABSTRACT

With the widespread implementation of antiretroviral therapy in many countries, the HIV/AIDS epidemic has declined. However, little is known about the prevalence of adherence rate to Highly Active Antiretroviral Therapy (HAART) in patients with HIV infection in China. This is the first meta-analysis of cross-sectional studies of treatment adherence (≥ 95%) to HAART in Chinese patients. Both English (PubMed, PsycINFO, EMBASE, and Web of Science) and Chinese (WanFang, CNKI, and SinoMed) databases were systematically and independently searched by three investigators. Studies with adherence rate estimates of HAART were included. Adherence rate estimates of each eligible study were extracted and pooled using the random-effects model. A total of 40 studies conducted in China were eligible and analyzed. The mean rate of ≥ 95% adherence to HAART was 81.1% (95%CI: 75.1%–88.0%, I² = 97.3%) at one week, 80.9% (95%CI: 74.7%–85.9%, I² = 96.6%) at one month, and 68.3% (95%CI: 46.1%–84.4%, I² = 97.1%) at 3 months or longer. Subgroup analyses revealed that samples with no gender predominance, low education level, middle economic region, rural area, older age (42.3 years), and recent publication (2013 or later) were correlated to higher HAART adherence. The average rate of HAART adherence was relatively high in China, which indicates effective HIV/AIDS policy, prevention and control measures. However, the HAART adherence rate decreased over the study time period.

KEYWORDS:

• HIV
• highly active antiretroviral therapy
• China
• meta-analysis
• cross-sectional studies

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by Beijing Municipal Administration of Hospitals’ Ascent Plan [grant number DFL20151801]; Beijing Municipal Administration of Hospitals Clinical Medicine Development of Special Funding Support [grant number ZYLX201607]; National Key Research & Development Program of China: [grant number 2016YFC1307200]; University of Macau: [grant number MYRG2015-00230-FHS; MYRG2016-00005-FHS].