{'fraction_non_alphanumeric': 0.02411412492229166, 'fraction_numerical': 0.011582632594967772, 'mean_word_length': 4.800721199468589, 'pattern_counts': {'":': 0, '<': 3, '<?xml version=': 0, '>': 1, 'https://': 4, 'lorem ipsum': 0, 'www.': 4, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 20, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Coital frequency and condom use in age-disparate partnerships involving women aged 15 to 24: evidence from a cross-sectional study in KwaZulu-Natal, South Africa

Objective This study examines the role of age-disparate partnerships on young women’s HIV risk by investigating coital frequency and condom use within age-disparate partnerships involving women aged 15 to 24. Design A community-based, cross-sectional study was conducted. Setting Participants were randomly selected using a two-stage random sampling method in uMgungundlovu district, KwaZulu-Natal, South Africa, between June 2014 and June 2015. Participants A total of 1306 15–24-year-old women in an ongoing heterosexual partnership were included in the analysis. Participants had to be a resident in the area for 12 months, and able to provide informed consent and speak one of the local languages (Zulu or English). Primary and secondary outcome measures Sexual frequency was assessed by asking participants how many times they had sex with each partner in the past 12 months. The degree of condomless sex within partnerships was assessed in the survey by asking participants how often they used a condom with their partners. Results Age-disparate partnerships were associated with a higher order category (once, 2–5, 6–10, 11–20, >20) of coital frequency (adjusted OR (aOR) 1.32, p<0.05, 95% CI 1.02 to 1.71) and with sex on more than 10 occasions (aOR 1.48, p<0.01, 95% CI 1.12 to 1.96) compared with age-similar partnerships. Age-disparate partnerships were also more likely to involve sex on more than 10 occasions with inconsistent condom use (aOR 1.43, p<0.05, 95% CI 1.04 to 1.96) in the previous 12 months. Conclusion The finding that increased sexual activity is positively associated with age-disparate partnerships adds to the evidence that age-disparate partnerships pose greater HIV risk for young women. Our study results indicate that interventions to reduce risky sexual behaviour within age-disparate partnerships remain relevant to reducing the high HIV incidence rates among adolescent girls and young women.

2) The authors state that age disparate relationships are higher risk because they involve older men in high-prevalence age categories (35)(36)(37)(38)(39)(40). This may not necessarily be true as these older men are more likely to be on ART. Furthermore, as the authors show, young women rarely report partnerships with men in this age category, being that they are 10-20 years older than the women (15)(16)(17)(18)(19)(20)(21)(22)(23)(24). The authors allude to another point, that sex with men who are perhaps 5-10 years older (the 25-34 y/o) may be the most likely to result in transmission, as these men are less likely to be virally suppressed if positive. This hypothesis was explained in our AIDS article (the first shared above).
3)The tables are a bit sparse. Tables 1 and 2 need extra demographic data on marital status, migration (if available), sexual violence, as well as partner age (in categories), partnership duration, partnership type, HIV status from testing, and all the sexual behavior outcomes of interest. 4) Total N for each category need (age disparate versus not) need to be included.

5)
The authors should take out the explanation of the overlapping sex frequency issue from the methods and discussion as it is a minor point. Other limitations including possible selection bias, missing data etc are more important. Perhaps the authors could just use a footnote on the tables to explain the issue.
6) The authors should add sample sizes used for each model in the logistic regression tables. Also, it would be nice to be reminded of the control variables in a table footnote.
9) The authors should discuss the reasons for including the specific confounders in their logistic regression and why the effect changes when they are included. It would be nice to see more of a complete summary of the descriptive statistics by partnership age disparate category.
10) The authors could provide more of a complete discussion of the limitations, namely, how the inherent biases might change the true effect sizes and whether the misclassification is differential or non-differential.
11) The authors could more completely contextualize their results within a wider literature on effective interventions in the discussion. Also sociological / cultural reasons for higher sexual risk behaviors in age-disparate relationships is needed. For example does it have more to do with the age of the male partner, or the age difference? This question needs to be addressed. The authors could also highlight that most relationships were same-aged and that relationships with much older men were rare. The authors could help settle this point which seems to be a pervasive misconception that older men are predatory and fueling the epidemic in young women.
12) There were many typos and unnecessary commas that need to be removed.

REVIEWER
Marie Stoner University of North Carolina, Chapel Hill, USA REVIEW RETURNED 30-May-2018

GENERAL COMMENTS
Overall, the paper was interesting and well done. It provides more insight into the relationship between age-disparate relationships and HIV risk by examining coital frequency and condom use in these partnerships. Some comments below.
1. The article is framed around risk of HIV in adolescent and young women but HIV negative women are only examined as a subgroup in a sensitivity analysis. It might make more sense to include this group as the population for the entire analysis because this is the group that the authors refer to as the target population in terms of the significance of these results. 2. Risk of HIV and likelihood of having an age-disparate relationship vary significantly by age over the age range 15-24. When girls are older and have completed school, they are more likely to look for long term relationships or marriage. It would add to the strength of the paper to examine associations stratified by age group to see if the relationship is different in younger versus older women. 3. The authors control for partnership duration and type of partnership. However, when thinking about risk of HIV, I still found myself wondering throughout the paper about how long term, monogamous partnerships are factoring into these results. Particularly as young women who are looking for marriage or longterm partnerships are more likely to select older men as partners. Monogamous, long-term partnerships would also have a higher coital frequency and are more likely to include unprotected sex (particularly if one knows their partner is HIV negative). It might strengthen the paper to also examine these associations only among young women who are not in long-term relationships with their partners or where they or their partner have concurrent relationships. 4. Did you evaluate the proportional odds assumption for the ordinal outcomes? I'm wondering if there might be a threshold effect where age-disparate doesn't have a linear effect on the outcome. Add more in the methods.

Minor
• Is there information available about partner or girl migration status? This might be important in terms of coital frequency and HIV risk.
• The reference period for coital frequency is 12 months, which is a really long period for remembering frequency for relationships that have ended or are long term. Is it possible to do a sensitivity analysis around reporting of frequency? Or add a longer discussion of how, specifically, misreporting might change the results.
• The authors use the standard cut-off for age-disparate which makes sense but is usually arbitrary. It might add to the conclusions to look at a one or ten-year change in age to determine more about if it makes a difference if partners are slightly older or if a larger age gap is important.
• Please clarify what you mean by this statement "Responses were reported within ranges in order to minimize social desirability bias." • Data were analyzed at the partnership level but it was unclear how multiple observations for the same girl are accounted for when controlling for individual level factors. Are you using GEE to account for correlation between multiple partners for the same girl?
• Clarify what is meant by this paragraph "Due to the way the number of sex acts were measured in the survey, we were unable to divide it by the precise duration of the relationship, which would have enabled us to annualise the coital frequency for those in partnerships less than 12 months old."

Response Reviewer 1
The authors should include discussion of three articles published on age-disparate relationships and risk of HIV acquisition. The first is a reanalysis of partnership age pairing data and risk of HIV acquisition from KZN and challenges the null results found in previous studies. This paper shows that while linear models may not show an association between partner age and HIV risk, certain partnership age pairings (i.e., those with young women and men 24-34 years of age) pose the greatest risk. Thus a linear model would not pick up on this result. This point can be added to the discussion instead of explaining the null result as due to more concurrency and less frequent sex (which the authors negate in their analysis. The second article that should be cited uses phylogenetic analysis to confirm the epidemiologic results of the first article. The third article confirms the results of your analysis and should also be included.
https://www.ncbi.nlm.nih.gov/pubmed/28590328, https://www.ncbi.nlm.nih.gov/pubmed/27914874 https://www.ncbi.nlm.nih.gov/pubmed/29587710 We have expanded the discussion section which now includes a review and acknowledgement of the articles listed by the reviewer. The studies which directly support our results have been cited.
The authors state that age disparate relationships are higher risk because they involve older men in high-prevalence age categories (35-40). This may not necessarily be true as these older men are more likely to be on ART. Furthermore, as the authors show, young women rarely report partnerships with men in this age category, being that they are 10-20 years older than the women (15-24). The authors allude to another point, that sex with men who are perhaps 5-10 years older (the 25-34 y/o) may be the most likely to result in transmission, as these men are less likely to be virally suppressed if positive. This hypothesis was explained in our AIDS article (https://www.ncbi.nlm.nih.gov/pubmed/28590328) We have clarified in the introduction that agedisparate partnerships are considered higher risk because older male partners are more likely to have HIV, and that we are focusing on older males across the spectrum and not just men in the 35-40 category. As the reviewer correctly points out one theory commonly posited for why age-disparate partnerships may not pose greater risk is that older HIV-positive partners may be on ART and therefore not pose an additional HIVinfection risk. It is a valuable suggestion to address this and we have added recent evidence showing that ART uptake has likely not mitigated risk from age-disparate partners as these partners are more likely to be HIV-positive and ART-naïve, and more likely to be HIV-positive with an unsuppressed viral load.
Specifically, the text now reads: "This risk to young women is driven by the higher HIV prevalence among older males, with HIV prevalence increasing steadily with age until peaking in approximately the 35-40 age cohort. Moreover, despite a positive association between age among men and both HIV-testing and antiretroviral therapy (ART) initiation, agedisparate male partners of young women are more likely to be HIV-positive and ART naïve, and to be HIV-positive with an unsuppressed viral load, resulting in an elevated risk of HIV infection. HIV-infection risk is amplified by risky sexual behaviour being more prevalent within agedisparate partnerships, including: inconsistent condom use; concurrent multiple sexual partnering; and transactional sex." The tables are a bit sparse. Tables 1 and 2 need extra demographic data on marital status, migration (if available), sexual violence, as well as partner age (in categories), partnership duration, partnership type, HIV status from testing, and all the sexual behavior outcomes of interest.
We agree that additional data on the sample would be useful. Table 1 has been expanded to include details on young women 1) HIV-status, 2) migration, 3) number of sources of HIV information in past 12 months. Additional partnerships details have also been included: 1) age of male partners, 2) nature of each partnership, 3) partnership duration. We do not report (or use) data on sexual violence as very few women reported being forced to have sex when they did not want to. Thank you for this suggestion. We have added the total N for each category. The authors should take out the explanation of the overlapping sex frequency issue from the methods and discussion as it is a minor point. Other limitations including possible selection bias, missing data etc are more important. Perhaps the authors could just use a footnote on the tables to explain the issue.
The discussion on the overlapping categories of the sex frequency variable has been removed from the measures section. The discussion has been put into the limitations section. We prefer to not make the footnote in the table as the footnotes will become even longer than they already are. The authors should add sample sizes used for each model in the logistic regression tables. Also, it would be nice to be reminded of the control variables in a table footnote.
We agree. The observations for each model have been added in an additional row in the tables. We have also included a description of all the control variables in the table notes. The chi2 column is unnecessary in table 2.
We have removed the categories and we have added the units of time.
The authors should discuss the reasons for including the specific confounders in their logistic regression and why the effect changes when they are included. It would be nice to see more of a We have moved the description of the control variables and the rationale for their inclusion to the analysis section. We believe this is a more natural place for this information, and will improve the flow by providing readers with details on the complete summary of the descriptive statistics by partnership age disparate category. model specification immediately after the models are introduced. The description has been expanded to include the justification for including a measure of migration, as suggested by the reviewers. Independently, none of the control variables had a large impact on the coefficients of interest. The largest effects were seen with the inclusion of the education and household income variables, but these only adjusted the coefficients by 0.03-0.07 (depending on the outcome of interest). The following text has been added to the results section to indicate that the adjusted model coefficients were not driven by any specific control variable: "The difference between the unadjusted and adjusted coefficients of interest for each outcome was not driven by any specific control variable, with each having a very small independent effect on the coefficients. While their effects were small, the inclusion of the education and the household income control variables had the strongest influenced on the models." The authors could provide more of a complete discussion of the limitations, namely, how the inherent biases might change the true effect sizes and whether the misclassification is differential or non-differential.
The authors have included a longer discussion on the limitations and have referenced particular studies that assess reporting on the number of sexual partners and reporting of the age of sexual partners. Although it should be acknowledged that it is not clear how these results will affect our estimates. Because we don't know whether the secondary partners that are less likely to be reported on are more likely to be age-disparate or age-similar.
See limitations section in the paper for the full discussion. The authors could more completely contextualize their results within a wider literature on effective interventions in the discussion. Also sociological / cultural reasons for higher sexual risk behaviors in age-disparate relationships is needed. For example does it have more to do with the age of the male partner, or the age difference? This question needs to be addressed. The authors could also highlight that most relationships were same-aged and that relationships with much older men were rare. The authors could help settle this point which seems to be a pervasive misconception that older men are predatory and fueling the epidemic in young women.
The discussion now includes a theory for higher sexual frequency. The paper does not say that older men are predatory. We have been careful to avoid phrasing and terminology that could give this impression. We have also identified subsequent epidemiological studies that have highlighted that certain partnership age pairings pose the greatest risk, independent of partnership age.
There were many typos and unnecessary commas that need to be removed.
We have read the manuscript carefully and believe that we have removed all the typos and unnecessary commas.

REVIEWER 2
The article is framed around risk of HIV in adolescent and young women but HIV negative women are only examined as a subgroup in a sensitivity analysis. It might make more sense to include this group as the population for the entire analysis because this is the group that the authors We recognize that the ideal design would require data from both partners and we would know who had been diagnosed HIV positive. The undiagnosed HIV-positive partner is important in the analysis as the behaviours within these partnerships count towards the risk by partnership refer to as the target population in terms of the significance of these results.
type. Roughly 15% of partnerships involved a women HIV-positive and undiagnosed.
HIV negative women are retained in the sensitivity analysis because it tests the results under the assumption that self-report of HIV-status could often be biased.
Restricting to HIV-negative could introduce selection bias in either direction if sexual behaviours among undiagnosed HIV-positive women varied significantly by partnership status.
Note that we have tightened the language significantly in this section in the expectation that it provides a clear rationale. Risk of HIV and likelihood of having an agedisparate relationship vary significantly by age over the age range 15-24. When girls are older and have completed school, they are more likely to look for long term relationships or marriage. It would add to the strength of the paper to examine associations stratified by age group to see if the relationship is different in younger versus older women.
We agree and ran additional models that included an interaction between age-group (15-19 vs 20-24) and age-disparate partnering. No statistically different associations were found across agegroups. We have added the following text to the results section: "Additional analyses (not presented) stratified by age-group (15-19 year-old vs 20-24 year-old women) found that the associations presented in Table 3 were not significantly different for younger compared to older women." The authors control for partnership duration and type of partnership. However, when thinking about risk of HIV, I still found myself wondering throughout the paper about how long term, monogamous partnerships are factoring into these results. Particularly as young women who are looking for marriage or long-term partnerships are more likely to select older men as partners. Monogamous, long-term partnerships would also have a higher coital frequency and are more likely to include unprotected sex (particularly if one knows their partner is HIV negative). It might strengthen the paper to also examine these associations only among young women who are not in long-term relationships with their partners or where they or their partner have concurrent relationships.
These are excellent ideas, which we have previously explored. There was very little variation in the nature of partnerships reported. Only 3% reported that their partner was a spouse, and only 4% reported that their partner was a casual partner. We have added these data to Table 1 to provide this information on the sample, which also indicates that such sub-analysis is not viable. There were also very few women who reported more than one current partnership at baseline. Additionally, we do not have data on whether the participants partners were monogamous or not.
Did you evaluate the proportional odds assumption for the ordinal outcomes? I'm wondering if there might be a threshold effect where age-disparate doesn't have a linear effect on the outcome. Add more in the methods.
The Brant (1990) test was used to determine whether the age-disparate relationship coefficients estimated in the ordered logistic models were similar across categories of sexual frequency and categories of sexual frequency and inconsistent condom use.
The proportional odds assumption was upheld for the sex frequency ordered logit model (p = 0.214) and the sex frequency and inconsistent condom use ordered logit model (p = 0.421). Similar results were found for the HIV negative sample only This will be added to the methods section.
Brant R. Assessing proportionality in the proportional odds model for ordinal logistic regression. Biometrics 1990; 46: 1171-1178 Is there information available about partner or girl migration status? This might be important in terms of coital frequency and HIV risk. This is an excellent idea. We have created a new variable that measures whether the participant reported being away from home over the last year for a period of greater than 1 consecutive month. We have described this variable in the methods section and included it in our multivariable models. The change to the key coefficients were very small. The results are therefore substantively similar using the revised model specification. The reference period for coital frequency is 12 months, which is a really long period for remembering frequency for relationships that have ended or are long term. Is it possible to do a sensitivity analysis around reporting of frequency? Or add a longer discussion of how, specifically, misreporting might change the results.
We do not include any partnerships that have ended. We do not, however, think that this recall bias would have influenced our results as there is no reason to believe that such recall bias would differ between women in age-similar and women in age-disparate partners. We have mentioned it in the limitations section that recall bias will affect all respondents.
The authors use the standard cut-off for agedisparate which makes sense but is usually arbitrary. It might add to the conclusions to look at a one or ten-year change in age to determine more about if it makes a difference if partners are slightly older or if a larger age gap is important.
We have looked at the differences between 5-9 vs 10+ years difference and there is not a simple pattern. Sometimes 5-9 (ref: age-similar) has a larger coefficient than 10+ (ref: age-similar). Sometimes the other way around. There are only 100 partnerships that are 10+ so the confidence intervals on this are quite large. Therefore we want to stick to the current age-disparate definition as this is the most common definition employed in analyses of older male partners in the literature. And the analysis looking specifically at 10+ older male partners involves larger uncertainties because of a small sample size. Please clarify what you mean by this statement "Responses were reported within ranges in order to minimize social desirability bias." This statement has been removed.
Data were analyzed at the partnership level but it was unclear how multiple observations for the same girl are accounted for when controlling for individual level factors. Are you using GEE to account for correlation between multiple partners for the same girl?
We adjusted standard errors for clustering at the enumeration area level to account for all potential within-cluster error correlation. This adjustment accounts for potential correlation between multiple observations for the same individuals. Further, for our main analysis sample, only 29 women reported multiple on-going partnerships. We have explicitly stated this number at the start of the results section as this small number will provide readers further confidence that results are not influenced by a large number of multiple partners reported by women. Clarify what is meant by this paragraph "Due to the way the number of sex acts were measured in the survey, we were unable to divide it by the precise duration of the relationship, which would have enabled us to annualise the coital frequency for those in partnerships less than 12 months old." We have clarified the sensitivity analysis as follows: "In a sensitivity analysis we excluded partnerships less than 12 months old because coital frequency was measured as the number of sex acts with a partner in the past 12 months. Accordingly the number of sex acts reported may not represent the same coital frequency for partnerships of less than a year duration compared to those of more than a year duration. This analysis therefore standardised the reference period for the number of reported sexual acts (ie, the past 12 months for all partnerships). Ideally, we would have divided the absolute number of sex acts by partnership duration to obtain an annualise measure of coital frequency for all partnerships, but this was not possible as coital frequency was captured in ranges and not as absolute numbers."

REVIEWER
Adam Akullian Institute for Disease Modeling REVIEW RETURNED 07-Sep-2018

GENERAL COMMENTS
This is a large improvement over the previous version. Well done.
There are a few outstanding changes that need to be made for this to be suitable for publication: 1) While it is good that the authors updated with conclusion, the introduction is still missing the three studies (two longitudinal and one phylogeneitc) showing that age-disparities ARE associated with increased risk of HIV acquisition in young women. This NEEDS to be included. It is false to say that cohort studies have not not found an association when there is mixed evidence. Please change this.
2) The authors state in the into that "Moreover, these agedisparate male partners of young women are also more likely to be ART naïve with an unsuppressed viral load." This is also NOT true. Older men are LESS likely to be ART naive with an unsuppressed viral load. The authors are misinterpreting the citation. Older men (or the partners of women in age-disparate partnerships) are more likely to be HIV positive and in turn may have higher prevalence of population viremia (meaning the probability of being viremic among all men in that category -infected or not). The authors need to correct this and remove citation 12, which doesn't state this.
3) I still don't understand why the authors spend so many words on the limitation of the error in categorizing partner age. That should be a short sentence, if that, and should be removed from the discussion, and placed in a footnote for a table to explain the error.
4) Finally, there is no discussion about whether the differences are attributed to the age-discrepancy itself or to attributes of older male partners. That should be discussed, as it seems that the two are often conflated. One is indicative of a power differential the other of attributes of a certain age group. This needs attention in the discussion.

Reviewers
Authors 1) While it is good that the authors updated with conclusion, the introduction is still missing the three studies (two longitudinal and one phylogeneitc) showing that age-disparities ARE associated with increased risk of HIV acquisition in young women. This NEEDS to be included. It is false to say that cohort studies have not found an association when there is mixed evidence. Please change this.
The three studies have been referenced and the conflicting nature of the evidence has been stated clearly. The authors have also added another reference titled: Age-disparate partnerships and incident HIV infection in adolescent girls and young women in rural South Africa: An HPTN 068 analysis.
2) The authors state in the into that "Moreover, these age-disparate male partners of young women are also more likely to be ART naïve with an unsuppressed viral load." This is also NOT true. Older men are LESS likely to be ART naive with an unsuppressed viral load. The authors are misinterpreting the citation. Older men (or the partners of women in age-disparate partnerships) are more likely to be HIV positive and in turn may have higher prevalence of population viremia (meaning the probability of being viremic among all men in that categoryinfected or not). The authors need to correct this and remove citation 12, which doesn't state this.
The citation has been removed and the sentence corrected.
3) I still don't understand why the authors spend so many words on the limitation of the error in categorizing partner age. That should be a short sentence, if that, and should be removed from the discussion, and placed in a footnote for a table to explain the error.
The limitation has been moved to the notes of Table 2. 4) Finally, there is no discussion about whether the differences are attributed to the agediscrepancy itself or to attributes of older male partners. That should be discussed, as it seems that the two are often conflated. One is indicative of a power differential the other of attributes of a certain age group. This needs attention in the discussion.
The following statement is included in the discussion: The increased sexual frequency that characterises age-disparate relationships is not fully understood and remains an area for future research. It would be valuable, for example, to examine whether the differences in coital frequency by partnership type can be attributed to the age-discrepancy itself or to attributes of older male partners

REVIEWER
Adam Akullian Institute for Disease Modeling REVIEW RETURNED 08-Nov-2018

GENERAL COMMENTS
Much improved on clarity. Well done.