Older adults at high risk of HIV infection in China: a systematic review and meta-analysis of observational studies

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Microbiology

Introduction

Human Immunodeficiency Virus (HIV) infection is a major public health challenge associated with high disease burden globally (Maartens, Celum & Lewin, 2014). In 2017, approximately 36.9 million people lived with HIV infection worldwide (UNAIDS, 2019). In China, the incidence of HIV was 4.1 per 100,000 individuals in 2018, which translates to approximately 56,993 newly infected persons (National Bureau of Statistics of China, 2018). Those who are at high risk of HIV infection include men who have sex with men (MSM) and younger adults (Knudson et al., 2018; Zhang et al., 2017b). In China, the highest HIV infection rate occurs in those aged between 20 and 40 years (Lu et al., 2008), but there has been an increasing prevalence in older adults recently, which is similar to trends in Western countries. For instance, around half of the people living with HIV were above 50 years old in the USA (High et al., 2012; Hosaka et al., 2019). In Europe, the number of adults aged 50 years or above living with HIV has been also growing (Seeley, 2017). A study in Chongqing, China found that the number of newly HIV infected persons aged over 50 years has increased six-fold from 1,091 in 2004 to 6,352 in 2015 (Zhang, Rongrong & Guohui, 2017a).

Epidemiological studies in China has found an increasing trend in the number and proportion of HIV infection among older adults (Xing et al., 2014). In the past decades, insufficient attention has been paid to older adults with HIV infection, with a lack of HIV risk reduction interventions (Cooperman, Arnsten & Klein, 2007; Crystal et al., 2003). Knowledge of safe sex activities and condom use are usually not addressed in older adults (Negin & Cumming, 2010), even though high risk sexual behaviors exist in this population (Crystal et al., 2003). In China, neglected sex education among older adults have been associated with unprotected sexual activities (Xing et al., 2014), which could increase the risk of HIV infection. On the other hand, the change in the age distribution of HIV infection in China could be partly due to the widespread use of free Highly Active Antiretroviral Therapy (HAART) in reducing transmission risk of HIV infection (Bhaskaran et al., 2008) among younger adults. Greater access to HIV clinics, free HAART treatment, and improved general healthcare service system in China have also increased their life expectancy therefore most are living to older adulthood (Greenbaum et al., 2008; Xing et al., 2014). These factors may also contribute to the growing proportion of older adults with HIV infection.

In order to develop appropriate strategies for HIV prevention and control, it is important to accurately determine the prevalence of HIV infection across different age groups. To date, no meta-analysis or systematic review of the prevalence of HIV infection in older Chinese adults has been published, which gave us impetus to conduct a meta-analysis to examine the prevalence and its associated factors in this population. In addition, we examined the association of demographic and clinical characteristics, such as sex and sexual orientation, with the prevalence of HIV infection in older adults using subgroup and meta-regression analyses. The target demographic and clinical characteristics were selected based on previous studies (Knudson et al., 2018; Zhang et al., 2017b).

Methods

Search strategy and selection criteria

This meta-analysis was performed according to the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) (Moher et al., 2009). Both International (PubMed, PsycINFO, Web of Science, and EMBASE) and Chinese (WanFang, CNKI and CQVIP) databases were systematically and independently searched by two investigators (Yuan Yang and Chang Chen) from their inception date up to May 1, 2020. The following search terms were used: (“HIV” OR “AIDS” OR “human immunodeficiency virus” OR “acquired immune deficiency syndrome”) AND (“epidemiology” OR “prevalence” OR “rate” OR “proportion”) AND (“old” OR “older” OR “elderly” OR “aged” OR “aging”) AND (“Chinese” OR “China”). Reference lists of eligible studies and relevant review articles were also hand-searched.

The inclusion criteria were studies that: (1) reported prevalence of HIV infection in older adults or provided information to calculate the prevalence. The diagnosis of HIV infection was based on study-defined criteria; (2) were cross-sectional or cohort studies (only baseline data were included) with meta-analyzable data; (3) were conducted in older adults (i.e., aged 50 years and older) in China. Case series, reviews, and meta-analyses were excluded.

Outcome measures

The outcome measure of the meta-analysis was the prevalence of HIV infection in older adults. For each study, the prevalence was calculated by the number of HIV-infected older adults divided by the total number of older adults.

Data extraction

Systematic literature search and data extraction were independently conducted by the same two investigators. The titles and abstracts of potential publications were screened separately by the same two investigators before the full texts were read for eligibility. Any inconsistencies in the process were discussed and resolved by a third reviewer (Yuan-Yuan Wang). The following information was extracted: year of publication, survey period, study site, sampling method, sample size and response rate, mean age, sex, education, occupation, province, rural or urban area, definition of older adults (e.g., above 50 years), and transmission route (e.g., commercial sex).

Quality assessment

The same two investigators independently evaluated the methodological assessment, using the critical appraisal for epidemiological studies (Loney et al., 1998) that contains 8 items covering three aspects: sampling, measurement and analysis. The total score of this instrument is 8; the total score of 7–8 was considered as ‘high quality’, 4–6 as ‘moderate quality’, and 0–3 as ‘low quality’ (Loney et al., 1998). Any inconsistencies were resolved by a discussion with a third investigator.

Data analysis

The Comprehensive Meta-Analysis software, Version 2.0 (http://www.meta-analysis.com/) and Open Meta-Analyst (http://www.cebm.brown.edu/openmeta/) were used to synthesize data (DerSimonian & Laird, 1986) in all the meta-analytic outcomes. Due to different sampling methods, study designs and demographic and clinical characteristics between studies, the random-effects model was used (DerSimonian & Laird, 1986). The heterogeneity of outcomes were assessed using I2, with I2 > 50% as significant heterogeneity (Higgins et al., 2003). Following the recommendation of the Cochrane handbook (Higgins et al., 2019) and other studies (Li et al., 2020; Xu et al., 2020; Yang et al., 2020), publication bias was assessed using the funnel plots and Begg’s test and Tweedie’s trim-and-fill analysis. All data analyses were 2 tailed, and the significant level was set at 0.05.

Subgroup and meta-regression analyses were performed to examine the moderating factors of HIV infection prevalence. Subgroup analyses were conducted according to the following categorical variables: (1) sexual orientation: MSM vs. not specified; (2) sex: male predominance (male percentage ≥ 60%) vs. no-predominance; (3) study site: hospital vs. community; (4) route of transmission: commercial sex vs. non-specified; (5) education: equal to and below primary school vs. above primary school education; (6) occupation: predominance of farmers (i.e., farmer percentage ≥ 60%) vs. no such predominance; (7) economic region: western vs. middle of vs. eastern region of China; (8) area: rural vs. urban; and (9) cut-off age for older adults: ≥50 years vs. ≥60 years, and (10) publication year: during and before 2014 vs. after 2014 (using median splitting method). Meta-regression analyses were conducted to examine the moderating effects of continuous variables (such as quality assessment score and study period) on the results when the number of included studies was at least 10.

Results

Literature search and study characteristics

A total of 3,641 publications were identified in the initial literature search. Finally, 46 studies with 363,399 subjects met the entry criteria and were included in the meta-analysis (Fig. 1); four studies were published in English (Chen et al., 2016; Feng et al., 2009; Ning et al., 2018; Xie et al., 2014), and the remaining were published in Chinese language. Table 1 shows the study characteristics. All studies were published between 2004 and 2018. Most studies (89%) used ≥ 50 years as cut-off age for older adults. Of the 46 studies, only one reported treatment information in HIV infected older adults, i.e., 53.75% of whom had HAART treatment (Ning et al., 2018).

PRISMA flow diagram.

Figure 1: PRISMA flow diagram.

Nine studies reported the HIV infection rate in all age groups (Chen et al., 2017; Chen et al., 2016; Chen et al., 2013; Du & Meng, 2016; Feng et al., 2009; Wang et al., 2018a; Zhao, Su & Jiang, 2015; Zhong et al., 2017; Zhu, Miu & Zhang, 2014), therefore only data in older adults were extracted for analyses; while five studies focused on older MSM adults. Thirteen studies reported transmission routes, while the remaining (71.7%) did not.

Prevalence of HIV infection in older adults and moderating factors

The pooled prevalence of HIV infection in older adults was 2.1% (95% CI [1.9%–2.3%], I2 = 99.3%, Fig. 2). The results of the subgroup analyses are presented in Table 2. MSM population, hospital population samples, publications after 2014, and studies conducted in the western region were significantly associated with higher HIV infection rate. Meta-regression analyses revealed that higher study quality was significantly associated with higher HIV prevalence (β = 0.84, p < 0.001, Fig. S1). Meta-regression analysis did not find any significant association between study periods and the prevalence of HIV infection (β = −0.03, p = 0.76).

Publication bias

Although funnel plot was visually asymmetrical (Fig. S2), Begg’s test did not find statistically significant publication bias (p = 0.21). The Duval and Tweedie trim-and-fill analysis suggests that 8 studies would need to be imputed to achieve an approximate normal error distribution. Including these 8 studies could lead to a lower prevalence of 0.096 (95% CI [0.094–0.099]).

Table 1:
Characteristics of studies included in this meta-analysis.
The first author (year) References Province ER Rural/ Urban Study period Study site Sample size Mean Age (yrs) Male (%) Education (primary school or illiterate %) Occupation (farmer;%) Transmission route Older adults defined age Study quality
1 Shao, 2018 Shao et al. (2018) Chongqing W Rural 04/2017–05/2017 Community 400 67 100 59% NR NR ≥60 5
2 Lin, 2018 Lin, Wu & Zheng (2018) Hainan E Urban 01/2011–12/2016 Hospital 1257 61.5 74.14 NR 52.94 NR ≥50 4
3 Lin, 2018 Lin et al. (2018) Guangxi W Rural 01/2016–08/2016 Community 468 NR 48.5 NR 97.01 NR ≥50 6
4 Li, 2018 Li et al. (2018a) Qinghai W Urban NR Community 150 NR 100 NR NR NR ≥50 5
5 Huang, 2018 Huang et al. (2018) Guangxi W Rural 08/2016–03/2017 Community 553 NR 49.55 62.39% 97.29 NR ≥50 5
6 Ning, 2018 Ning et al. (2018) Shanghai E Urban 01/2008–12/2014 Community 12910 59.3 100 NR NR NR ≥50 5
7 Zhong, 2017 Zhong et al. (2017) Sichuan W Rural 2014–2016 Hospital 576 NR NR NR NR NR ≥50 5
8 Zhang, 2017 Chen et al. (2017) Jiangsu E Both 10/2015–03/2016 Community 200 68.42 100 73.50% NR NR ≥50 5
9 Yu, 2017 Yu (2017) Guangxi W Both 10/2015–01/2016 Community 461 58.82 100 22.30% 10.4 Commercial sex ≥50 6
10 Xu, 2017 Xu & Zhu (2017) Guangdong E Urban 01/2016–04/2016 Community 528 NR 100 NR NR NR ≥50 5
11 Maiwulani, 2017 Maiwulani et al. (2017) Xinjiang W Urban 01/2015–12/2015 Hospital 3830 NR 54.31 41.90% NR NR ≥50 5
12 Liu, 2017 Liu et al. (2017) Jiangsu E Urban 04/2013–06/2015 Hospital 174 57.15 100 11.50% NR NR ≥50 4
13 Deng, 2017 Deng et al. (2017) Guangxi W both 10/2012–12/2012 Community 4048 NR 100 NR NR Commercial sex ≥50 5
14 Chen, 2017 Chen et al. (2017) Guangdong E Urban 2010–2016 Hospital 165 NR NR NR NR NR ≥50 5
15 Zhu, 2016 Zhu et al. (2016) Jiangsu E Rural NR Community 2860 71.75 48.39 90.07% NR NR ≥65 6
16 Su, 2016 Su et al. (2016) Yunnan W Both 01/2011–12/2013 Hospital 26807 NR 60.3 60.40% NR NR ≥50 5
17 Shi, 2016 Shi et al. (2016) Jiangsu E Both 2010–2014 Community 1185 NR 100 52.83% NR NR ≥50 5
18 Liu, 2016 Liu et al. (2016) Hubei M both 12/2014–12/2014 Community 601 65.7 100 59.80% 61.50% NR ≥50 6
19 Hong, 2016 Hong, Zhang & Zhang (2016) Zhejiang E both 03/2014–08/2014 Community 400 64.1 100 73.50% NR NR ≥50 4
20 Du, 2016 Du & Meng (2016) Sichuan W both 01/2009–12/2014 Community 372 NR NR NR NR NR ≥50 4
21 Chen Z, 2016 Chen et al. (2016b) Chongqing W Urban 04/2015–05/2015 Community 599 NR 40.23 29.55% 13.40% NR ≥60 6
22 Chen Y, 2016 Chen et al. (2016a) Guangxi W both 2010–2015 Community 14105 NR 100 NR NR Commercial sex ≥50 4
23 Zhou, 2015 Zhou et al. (2015) Shanghai E Urban 05/2011–04/2013 Community 165 58.7 100 NR NR NR ≥50 5
24 Wu, 2015 Wu et al. (2015) Guangxi W both 10/2012–04/2013 Community 1761 64.23 100 74.50% 76.2 Commercial sex ≥50 4
25 Qin, 2015 Qin et al. (2015) Guangxi W Both 2012 Community 430 61.06 100 75.80% 90 Commercial sex ≥50 4
26 Ma, 2015 Ma et al. (2015) Chongqing W Urban 01/2010–12/2014 Hospital 832 60.1 69.11 37.86% 43.51 NR ≥50 4
27 Lu, 2015 Lu et al. (2015) Guangxi W both 10/2012–04/2013 Community 1236 68.42 100 86.92% 88.11 Commercial sex ≥60 4
28 Li, 2015 Li et al. (2015) Jiangxi M NR 01/2013–12/2013 Community 405 NR 65.68 56.30% NR NR ≥50 6
29 Zhu Y, 2014 Zhu, Miu & Zhang (2014) Yunnan W NR 01/2013–12/2013 Community 73 NR NR NR NR NR ≥50 5
30 Zhu J, 2014 Zhu et al. (2014) Guangxi W both NR Community 377 61.5 100 73.80% 85.4 Commercial sex ≥50 5
31 Wang, 2014 Wang (2014) Guangxi W both 10/2012–04/2014 Community 848 56.6 100 80.20% 82.7 Commercial sex ≥50 5
32 Min, 2014 Min et al. (2014) Yunnan W both NR Community 210 62 100 NR NR sex ≥50 4
33 Lu, 2014 Lu et al. (2014) Guangxi W both 10/2012–04/2013 Community 2056 62.28 100 75.73% 78.79 Commercial sex ≥50 4
34 Li, 2014 Li, Wu & Chen (2014) Zhejiang E NR 2006–2012 Community 3860 NR NR NR NR NR ≥50 5
35 Dou, 2014 Dou (2014) Anhui E Urban 2010–2014 Hospital 427 62.34 100 NR NR NR ≥50 5
36 Xie, 2014 Xie et al. (2014) Zhejiang E NR 03/2012–08/2012 Community 215441 63.51 42.26 NR NR NR ≥50 6
37 Zhou, 2013 Zhou et al. (2013) Shanghai E Urban 03/2011–09/2011 Hospital 157 60.1 100 15.90% NR NR ≥50 5
38 Chen, 2013 Chen et al. (2013) Guangxi W both 04/2012–07/2012 Community 2305 NR 100 NR NR Commercial sex ≥50 4
39 Feng, 2009 Feng et al. (2009) Chongqing W NR 07/2006–09/2006, 07/2007–09/2007 Community 46 NR 100 NR NR NR >50 4
40 Liu, 2004 Liu et al. (2004) Hubei M both 01/1999–04/2002 Hospital 902 NR NR NR NR NR ≥60 5
41 Zhao, 2015 Zhao, Su & Jiang (2015) Liaoning M NR 01/2011–12/2013 Hospital 1217 NR NR NR NR NR ≥50 4
42 Wu, 2013 Wu et al. (2013) Guangxi W NR NR Community 414 NR 100 77.05% 96.14 Commercial sex ≥50 4
43 Li, 2018 Li et al. (2018b) Sichuan W NR 04/2014–12/2015 Community 363 NR 100 NR NR Commercial sex ≥50 4
44 Fu, 2013 Fu et al. (2013) Yunnan W NR 01/2008–02/2013 Hospital 842 59.35 64.75 65.82% 74.11 NR ≥50 4
45 Pan, 2014 Pan, Xie & Xu (2014) Guangdong E NR 06/2011–05/2013 Hospital 184 NR 65.21 NR NR NR ≥50 4
46 Wang, 2018 Wang et al. (2018a),Wang et al. (2018b) Henan M NR 01/2013–12/2015 Hospital 56199 NR 52.22 NR NR NR ≥50 4
DOI: 10.7717/peerj.9731/table-1

Notes:

ER

Economic Regions

E

East

M

Middle

W

West

U

Urban

R

Rural

NR

Not recorded

Discussion

This was the first meta-analysis to examine the prevalence of HIV infection in older adults in China. The meta-analysis revealed that the pooled prevalence of HIV infection in older Chinese adults was 2.1%, which was substantially higher than the figure reported in the Chinese general population (0.05%) (National Bureau of Statistics of China, 2018). The high HIV infection rate could be due to several reasons. The life expectancy of HIV-infected adults has been significantly prolonged due to widespread use of HAART (Bhaskaran et al., 2008; Greenbaum et al., 2008; Xing et al., 2014); e.g., the National Free Antiretroviral Treatment Program (NFATP) has covered more than 97% of HIV-infected people in China (Zhang et al., 2009). The high HAART adherence rate in Chinese HIV patients, as confirmed by a recent meta-analysis (Wang et al., 2018b), would be expected to increase life expectancy and many patients are living into their older adulthood. Furthermore, many studies have indicated increasing transmission via commercial sexual activities among older Chinese men after retirement as a major reason for HIV infection (Wang et al., 2014; Zhou et al., 2014). It has been suggested that prevention of HIV transmission among older MSM should be an urgent priority in China’s HIV/AIDS strategy (Ning et al., 2018).

Pooled HIV prevalence of the included studies.

Figure 2: Pooled HIV prevalence of the included studies.

The high proportion of HIV infection in older adults is growing major public health challenge in China. Compared to younger adults, physical and psychiatric comorbidities, such as pneumonia, depression and insomnia, are usually more common in HIV-infected older adults (Ding et al., 2017), which could lead to heavy personal, family and economic burden. Therefore, appropriate allocation of healthcare resources and developing effective preventive strategies for HIV-infected older adults in China should be considered (Xing et al., 2014).

Table 2:
Subgroup analysis of HIV prevalence in older adults in China.
Subgroup Number of studies Sample size Number of cases Prevalence (%) 95% CI I2 (% with P-value)
1. Sexual orientation: MSM population 5 1,720 178 11.8 8.5–15 59.24 (<0.05)
Not specified 41 361,679 5,560 2.0 1.8–2.2 99.4 (<0.001)
2. Sex: Male predominance (≥60%) 32 76,284 5,159 4.1 2.8–5.4 99.2 (<0.001)
No predominance 4 7,711 204 1.7 0.4–3.9 98.6 (<0.001)
3. Study site: Hospital 14 93,569 4,587 7.5 4.5–10.4 99.8 (<0.001)
Community 32 269,830 1,151 1.5 1.3–1.8 97.4 (<0.001)
4. Route of transmission: Commercial sex 12 28,404 610 2.2 1.8–2.6 71.3 (<0.001)
Not specified 33 334,785 5,110 2.0 1.8–2.2 99.5 (<0.001)
5. Education: Primary school and below (≥60%) 13 38,784 4,130 3.4 0.6–6.1 99.7 (<0.001)
Above primary school (≥60%) 8 7,167 205 3.9 2.1–5.8 96.8 (<0.001)
6. Occupation: Farmer predominance (≥60%) 11 9,586 283 2.6 1.7–3.5 90.2 (<0.001)
No predominance 4 3,149 246 6.9 0.2–11.5 97.0 (<0.001)
7. Economic Region: West 26 64,162 5,152 6.0 4.2–7.9 99.3 (<0.001)
Middle 5 59, 324 46 0.5 0.0–1.0 87.1 (<0.001)
East 15 239,913 540 1.0 0.7–1.3 97.5 (<0.001)
8. Area: Rural 5 4, 857 195 4.8 2.6–7.1 98.6 (<0.001)
Urban 12 21,194 732 5.8 4.3–7.3 97.2 (<0.001)
Urban and Rural 18 58,304 4,630 3.8 1.8–5.7 99.5 (<0.001)
9. Defined age for older adults (years): ≥50 41 357,402 5,654 2.4 2.2–2.5 99.4 (<0.001)
≥60 5 5,997 84 1.4 0.6–2.3 95.4 (<0.001)
10. Publication yeara: In or before 2014 15 22,8142 305 2.1 1.5–2.7 95.4 (<0.001)
After 2014 31 135,257 5,433 3.6 3.1–4.1 99.5 (<0.001)
DOI: 10.7717/peerj.9731/table-2

Notes:

Analyzed using a median splitting method.

Consistent with previous findings on HIV prevalence in China (Zhang et al., 2013), we found in this meta-analysis that MSM was associated with a higher risk of HIV infection; the HIV prevalence in MSM older adults was 11.8%, which was the highest among all subgroups. Compared to community populations, hospital population samples were significantly associated with higher HIV infection rate, which is probably because older adults with HIV infection were more likely to receive HIV testing than those in the community. Compared to middle and eastern economic regions, HIV infection prevalence in older adults was significantly higher in the western region of China, being less developed than other parts of China. Therefore, the lack of access to HIV treatment and prevention measures in the western region could be associated with higher HIV infection rate. Due to degradation of traditional Chinese family structure and lack of family support, retired older men are also more likely to have engaged in commercial sex, particularly in under-developed western regions of China (Huang, Maman & Pan, 2012).

Unexpectedly, commercial sex as the transmission route was not significantly associated with higher HIV infection rate. This appears inconsistent with previous findings that commercial sex is a major route for HIV infection transmission among older Chinese men (Wang et al., 2014; Zhou et al., 2014). Studies published after 2014 were significantly associated with higher HIV infection rate, which we were unable to explain adequately. However, we found that higher study quality was significantly associated with higher HIV prevalence. Due to sigma and discrimination associated with HIV/AIDS, many sufferers, particularly older adults in China usually deny or conceal their diagnosis in order to avoid “loss of face”. High quality studies may identify patients more systematically, and obtain a more accurate and often higher rate HIV infection.

There were several limitations in this meta-analysis. First, similar to other meta-analyses of epidemiological studies (Liu et al., 2016; Long et al., 2014; Wang et al., 2018b; Winsper et al., 2013), there was substantial heterogeneity, although subgroup analyses were performed. The heterogeneity may be associated with different sampling methods, study designs, diagnostic criteria of HIV infection and demographic and clinical characteristics between studies. Second, most studies did not report the transmission route, therefore further sophisticated analyses could not be conducted. Third, due to the cross-sectional design of included studies, the causal relationship between HIV infection and related variables could not be explored.

In conclusion, this meta-analysis showed that the prevalence of HIV infection in older adult population is significantly higher than the general population in China. Attention should be given to this urgent public health issue, and effective HIV/AIDS preventive, screening and treatment measures are warranted in this population.

Supplemental Information

Meta-regression for study quality and HIV prevalence

DOI: 10.7717/peerj.9731/supp-1

Funnel plot of standard error by logit event rate

DOI: 10.7717/peerj.9731/supp-2

Quality assessment for included studies

DOI: 10.7717/peerj.9731/supp-3

Rationale and contribution

DOI: 10.7717/peerj.9731/supp-4

PRISMA checklist

DOI: 10.7717/peerj.9731/supp-5
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