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Anal sex popular in some countries

Anal sex popular in some countries

Find articles by Rebecca F. Received Apr 14; Accepted Dec We aimed to determine how common and frequent heterosexual AI is in South Africa. Stratified random-effects meta-analysis by sub-groups was used to produce pooled estimates and assess the influence of participant and study characteristics on AI prevalence. Of 41 included studies, 31 reported on AI prevalence and 14 on frequency, over various recall periods.

AI prevalence was high across different recall periods for sexually active general-risk populations e. Prevalence was higher in studies using more confidential interview methods. Among general and higher-risk populations, 1. AI acts were as likely to be condom protected as vaginal acts. Reported heterosexual AI is common but variable among South Africans.

Nationally and regionally representative sexual behaviour studies that use standardized recall periods and confidential interview methods, to aid comparison across studies and minimize reporting bias, are needed. Anal intercourse, heterosexual, sexual behaviour, South Africa Introduction The increased risk of HIV transmission during receptive anal intercourse AI compared to receptive vaginal intercourse VI is long established, yet its role as a determinant of epidemics driven by sex between men and women heterosexual sex in different settings remains uncertain [ 1 — 6 ].

Thus, even low frequency of UAI could contribute significantly to HIV transmission among those practising heterosexual sex [ 8 ]. The risks of AI have often been omitted from sexual health messaging targeted at people who have heterosexual sex.

This has potentially led to the misconception that UAI is safe and may have driven lower condom use during AI among heterosexuals [ 9 — 11 ]. Previous modelling studies also suggest that even a small fraction of UAI could not only influence HIV spread but also reduce the potential impact of specific interventions such as topical vaginal microbicide VMB [ 2 , 4 , 8 , 12 ]. In contrast, tenofovir, the active pharmaceutical ingredient in oral pre-exposure prophylaxis PrEP has been found at higher concentration in rectal than vaginal tissue, suggesting that PrEP may be more protective during receptive AI than VI [ 13 — 17 ].

South Africa is an important setting to examine patterns of heterosexual AI, as it has the largest HIV epidemic driven by heterosexual sex in the world [ 18 ]. Its epidemic is among the most researched in sub-Saharan Africa. However, the high prevalence of HIV infection, particularly among young women, and the extent to which AI plays a role, are not well understood [ 19 , 20 ].

Reporting accuracy is also a particular concern for AI compared to VI throughout sub-Saharan Africa not only because, as in many countries worldwide, it is perceived as less socially acceptable and thus liable to underreporting [ 21 — 23 ], but also because local languages refer to AI only in euphemistic terms which are subject to misinterpretation [ 10 , 24 — 26 ].

Understanding the impact of study characteristics on estimates of AI is critical to inform future study designs to more accurately capture sensitive data. This paper presents our systematic review of evidence from published literature on self-reported sexual behaviour to determine how common i.

We also describe how AI practices vary by risk group, age, types of partners, setting and over time. This review will be useful to improve our understanding of AI practices, inform prevention messages, and highlight knowledge gaps. Key parameter estimates derived from this review can be used in mathematical models to explore the contribution of AI to the HIV epidemic and assess the influence of AI on the predicted effectiveness of prevention interventions.

We first screened titles, discarding those that were obviously irrelevant, then screened abstracts and retrieved full-text articles if any heterosexual sexual behaviour was reported.

Full-text articles were screened for quantitative data on AI practices as described below. We scanned the bibliographies of all included articles for further relevant citations. Additionally, we searched for relevant data from national surveys not reported in peer-reviewed journals, which we identified through a Google internet search. We included reports from cross-sectional, cohort and randomized controlled trials RCTs.

Articles which explicitly reported including men who have sex with men MSM for which data on heterosexual AI was indistinguishable from homosexual AI, which were conducted wholly or partly outside of South Africa and which did not contain AI data were excluded. Data extraction Our four main outcomes of interest were i AI prevalence the proportion of participants practising AI among sexually active respondents , ii monthly frequency of sex acts by type, iii fraction of all sex acts and all unprotected sex acts which are AI and UAI, and iv fraction of AI and VI acts that are unprotected by condoms.

Outcomes were stratified by gender men, women where possible no eligible studies reported any outcome for transgender respondents. When directly reported, we extracted these estimates, otherwise we extracted the relevant information to derive them when available.

We also extracted information on key participant and study characteristics gender, survey year, population, mean age, urban or rural and province , including factors reflecting study quality interview method, study design, sampling method, response rate, survey language and whether heterosexuals only were included.

Additionally, we identified the location in the article where AI was first mentioned title, abstract or main text and used this to explore publication bias, as papers may report AI behaviour more prominently within the article if the practice is common. We extracted only baseline data from cohort and RCT studies as we were interested in AI practice in the absence of possible intervention and to minimize potential Hawthorne effect.

Where data from the same or overlapping study populations were reported in more than one article, the publication with the largest sample size or with the most information on AI if the sample size was the same was included.

We contacted authors of included studies when key variables of interest interview method, recall period for either AI prevalence or frequency or the CI or SD of number of sex acts were not reported.

Samples recruited from communities, schools, health clinics, shebeens informal drinking establishments and similar were classified as general-risk populations, while sexually transmitted infection STI clinic patients, female sex workers FSW , their clients, and HIV-infected individuals were classified as higher-risk populations.

Relevant information was initially extracted or derived into a standard datasheet by BO and double checked by JE. Additional details on methods are provided in supplementary material. Data synthesis and statistical methods AI prevalence Extracted data were used to derive AI prevalence estimates and CIs amongst sexually active participants defined as those reporting practising VI i. We produced forest plots of study estimates by recall period, presenting all results from general and higher-risk populations separately.

Based on our previous review on AI practices among youth [ 30 ], we anticipated substantial heterogeneity across estimates and we therefore pooled results using random-effects models and conducted extensive sub-group analyses to explore the influence of participant and study characteristics and study quality [ 31 — 33 ].

We examined the effect of participant and study characteristics on pooled AI prevalence estimates by conducting sub-group analyses for each recall period; analyses were restricted to recall periods with at least five studies. We examined time trends by dichotomizing at the median survey year of included studies Measures of study quality and potential sources of bias were also tested using sub-group analyses.

Heterogeneity across study estimates was investigated using I2 statistics [ 38 , 39 ]. Frequency data To facilitate comparison across studies, we standardized sex act frequency estimates to one month Supplement B1. Results Search results Supplementary Figure 1 summarizes the study selection procedure and search results.

Of the titles initially identified, 41 articles were included. Most articles were identified from the database search, with three included articles identified through reference scanning and none through the internet search for grey literature. Additional information was obtained from three of the eleven authors contacted. A list of excluded articles is available on request. Study characteristics Table 1 provides a summary of the participant and study characteristics and markers of study quality.

Details of each individual study are available in Supplementary Table S1. Of the 41 studies included, 29 and 14 were conducted among general and higher-risk populations, respectively, including two studies which reported on both risk groups separately [ 40 , 41 ].

AI prevalence and AI frequency were reported over various recall periods by 31 including four studies reporting UAI prevalence only [ 42 — 45 ] and 14 studies, respectively. No studies reported on lubricant use or condom breakage during AI.

Summary of study and participant characteristics and study quality of included studies.

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Anal sex popular in some countries

Find articles by Rebecca F. Received Apr 14; Accepted Dec We aimed to determine how common and frequent heterosexual AI is in South Africa. Stratified random-effects meta-analysis by sub-groups was used to produce pooled estimates and assess the influence of participant and study characteristics on AI prevalence. Of 41 included studies, 31 reported on AI prevalence and 14 on frequency, over various recall periods. AI prevalence was high across different recall periods for sexually active general-risk populations e.

Prevalence was higher in studies using more confidential interview methods. Among general and higher-risk populations, 1. AI acts were as likely to be condom protected as vaginal acts. Reported heterosexual AI is common but variable among South Africans. Nationally and regionally representative sexual behaviour studies that use standardized recall periods and confidential interview methods, to aid comparison across studies and minimize reporting bias, are needed.

Anal intercourse, heterosexual, sexual behaviour, South Africa Introduction The increased risk of HIV transmission during receptive anal intercourse AI compared to receptive vaginal intercourse VI is long established, yet its role as a determinant of epidemics driven by sex between men and women heterosexual sex in different settings remains uncertain [ 1 — 6 ].

Thus, even low frequency of UAI could contribute significantly to HIV transmission among those practising heterosexual sex [ 8 ]. The risks of AI have often been omitted from sexual health messaging targeted at people who have heterosexual sex.

This has potentially led to the misconception that UAI is safe and may have driven lower condom use during AI among heterosexuals [ 9 — 11 ]. Previous modelling studies also suggest that even a small fraction of UAI could not only influence HIV spread but also reduce the potential impact of specific interventions such as topical vaginal microbicide VMB [ 2 , 4 , 8 , 12 ]. In contrast, tenofovir, the active pharmaceutical ingredient in oral pre-exposure prophylaxis PrEP has been found at higher concentration in rectal than vaginal tissue, suggesting that PrEP may be more protective during receptive AI than VI [ 13 — 17 ].

South Africa is an important setting to examine patterns of heterosexual AI, as it has the largest HIV epidemic driven by heterosexual sex in the world [ 18 ]. Its epidemic is among the most researched in sub-Saharan Africa.

However, the high prevalence of HIV infection, particularly among young women, and the extent to which AI plays a role, are not well understood [ 19 , 20 ].

Reporting accuracy is also a particular concern for AI compared to VI throughout sub-Saharan Africa not only because, as in many countries worldwide, it is perceived as less socially acceptable and thus liable to underreporting [ 21 — 23 ], but also because local languages refer to AI only in euphemistic terms which are subject to misinterpretation [ 10 , 24 — 26 ]. Understanding the impact of study characteristics on estimates of AI is critical to inform future study designs to more accurately capture sensitive data.

This paper presents our systematic review of evidence from published literature on self-reported sexual behaviour to determine how common i. We also describe how AI practices vary by risk group, age, types of partners, setting and over time. This review will be useful to improve our understanding of AI practices, inform prevention messages, and highlight knowledge gaps.

Key parameter estimates derived from this review can be used in mathematical models to explore the contribution of AI to the HIV epidemic and assess the influence of AI on the predicted effectiveness of prevention interventions.

We first screened titles, discarding those that were obviously irrelevant, then screened abstracts and retrieved full-text articles if any heterosexual sexual behaviour was reported. Full-text articles were screened for quantitative data on AI practices as described below. We scanned the bibliographies of all included articles for further relevant citations. Additionally, we searched for relevant data from national surveys not reported in peer-reviewed journals, which we identified through a Google internet search.

We included reports from cross-sectional, cohort and randomized controlled trials RCTs. Articles which explicitly reported including men who have sex with men MSM for which data on heterosexual AI was indistinguishable from homosexual AI, which were conducted wholly or partly outside of South Africa and which did not contain AI data were excluded.

Data extraction Our four main outcomes of interest were i AI prevalence the proportion of participants practising AI among sexually active respondents , ii monthly frequency of sex acts by type, iii fraction of all sex acts and all unprotected sex acts which are AI and UAI, and iv fraction of AI and VI acts that are unprotected by condoms. Outcomes were stratified by gender men, women where possible no eligible studies reported any outcome for transgender respondents.

When directly reported, we extracted these estimates, otherwise we extracted the relevant information to derive them when available. We also extracted information on key participant and study characteristics gender, survey year, population, mean age, urban or rural and province , including factors reflecting study quality interview method, study design, sampling method, response rate, survey language and whether heterosexuals only were included.

Additionally, we identified the location in the article where AI was first mentioned title, abstract or main text and used this to explore publication bias, as papers may report AI behaviour more prominently within the article if the practice is common. We extracted only baseline data from cohort and RCT studies as we were interested in AI practice in the absence of possible intervention and to minimize potential Hawthorne effect.

Where data from the same or overlapping study populations were reported in more than one article, the publication with the largest sample size or with the most information on AI if the sample size was the same was included.

We contacted authors of included studies when key variables of interest interview method, recall period for either AI prevalence or frequency or the CI or SD of number of sex acts were not reported. Samples recruited from communities, schools, health clinics, shebeens informal drinking establishments and similar were classified as general-risk populations, while sexually transmitted infection STI clinic patients, female sex workers FSW , their clients, and HIV-infected individuals were classified as higher-risk populations.

Relevant information was initially extracted or derived into a standard datasheet by BO and double checked by JE. Additional details on methods are provided in supplementary material. Data synthesis and statistical methods AI prevalence Extracted data were used to derive AI prevalence estimates and CIs amongst sexually active participants defined as those reporting practising VI i.

We produced forest plots of study estimates by recall period, presenting all results from general and higher-risk populations separately. Based on our previous review on AI practices among youth [ 30 ], we anticipated substantial heterogeneity across estimates and we therefore pooled results using random-effects models and conducted extensive sub-group analyses to explore the influence of participant and study characteristics and study quality [ 31 — 33 ].

We examined the effect of participant and study characteristics on pooled AI prevalence estimates by conducting sub-group analyses for each recall period; analyses were restricted to recall periods with at least five studies. We examined time trends by dichotomizing at the median survey year of included studies Measures of study quality and potential sources of bias were also tested using sub-group analyses.

Heterogeneity across study estimates was investigated using I2 statistics [ 38 , 39 ]. Frequency data To facilitate comparison across studies, we standardized sex act frequency estimates to one month Supplement B1.

Results Search results Supplementary Figure 1 summarizes the study selection procedure and search results. Of the titles initially identified, 41 articles were included. Most articles were identified from the database search, with three included articles identified through reference scanning and none through the internet search for grey literature. Additional information was obtained from three of the eleven authors contacted. A list of excluded articles is available on request.

Study characteristics Table 1 provides a summary of the participant and study characteristics and markers of study quality. Details of each individual study are available in Supplementary Table S1. Of the 41 studies included, 29 and 14 were conducted among general and higher-risk populations, respectively, including two studies which reported on both risk groups separately [ 40 , 41 ]. AI prevalence and AI frequency were reported over various recall periods by 31 including four studies reporting UAI prevalence only [ 42 — 45 ] and 14 studies, respectively.

No studies reported on lubricant use or condom breakage during AI. Summary of study and participant characteristics and study quality of included studies.

Anal sex popular in some countries

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2 Comments

  1. Data synthesis and statistical methods AI prevalence Extracted data were used to derive AI prevalence estimates and CIs amongst sexually active participants defined as those reporting practising VI i. Results Search results Supplementary Figure 1 summarizes the study selection procedure and search results. Received Apr 14; Accepted Dec

  2. Of 41 included studies, 31 reported on AI prevalence and 14 on frequency, over various recall periods. The risks of AI have often been omitted from sexual health messaging targeted at people who have heterosexual sex.

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