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PLOS One logoLink to PLOS One
. 2020 Oct 7;15(10):e0240247. doi: 10.1371/journal.pone.0240247

Semi-parametric model for timing of first childbirth after HIV diagnosis among women of childbearing age in Ibadan, Nigeria

Joshua Odunayo Akinyemi 1,2, Rotimi Felix Afolabi 1,3,*, Olutosin Alaba Awolude 4
Editor: Kannan Navaneetham5
PMCID: PMC7540879  PMID: 33027315

Abstract

Background

HIV diagnosis is a watershed in women’s childbearing experience. It is usually accompanied by the fear of death and stigmatisation. Women diagnosed of HIV are often sceptical about pregnancy. Meanwhile, availability of antiretroviral treatments has impacted positively on childbearing experience among women living with HIV. We therefore investigated the timing of first childbirth after HIV diagnosis and its determinants among women in Ibadan, Nigeria.

Methods

We extracted and analysed data from a 2015 cross-sectional study on childbearing progression among 933 women living with HIV and receiving care at University College Hospital, Ibadan, Nigeria. Extended Cox proportional hazards regression, a semi-parametric event history model was used at 5% significance level.

Results

The women’s mean age was 38.1 (± SD = 6.1) years and the median time to first birth after HIV diagnosis (FBI_HIV) was 8 years. The likelihood of first birth after HIV diagnosis was lower among women who desired more children (HR = 0.63, CI: 0.51–0.78). Women whose partners had primary and secondary education respectively were about 2.3 times more likely to shorten FBI_HIV compared to those whose partners had no formal education. Knowledge of partner’s HIV-positive status (HR = 1.42, CI: 1.04,1.93) increased the likelihood of having a first birth after HIV diagnosis. Older age, longer duration on ART and a higher number of children at diagnosis were associated with a declined hazard of first birth after HIV diagnosis.

Conclusions

The median time to first childbirth after HIV diagnosis was long. Partner’s HIV-positive status and higher educational attainment were associated with early childbearing after HIV diagnosis.

Introduction

HIV prevalence remains a public health challenge in Nigeria. As the second epicentre of HIV infection globally, Nigeria contributed about 75% of new HIV infections in West and Central Africa in 2016 [1]. According to the recent UNAIDS report, the national HIV prevalence among adult aged 15–49 years is 1.5% [2], of which women have considerable higher prevalence of 1.9% compared to men [3]. Many of those individuals living with HIV are women who desire to affirm their motherhood. Nearly 50% and 75% of the women respectively desired more children according to studies conducted in Ethiopia and United Kingdom [4, 5].

Besides, as suggested by a study conducted in Malawi, women living with HIV (WLWH) desired to have their own children as a way of affirming their capacity for childbearing [6]. Meanwhile, a long duration on ART has been established to influence women’s desire for children [7]. Even in the era of effective ART, empirical studies have established that HIV diagnosis may significantly influence women’s decision and timing to have the next child birth or otherwise [811]. Child’s birth may boost motherhood status among WLWH. Meanwhile, birth intervals could impact on the health of the mother and new-born in that sufficient spacing may avert adverse maternal and child outcomes among WLWH [1214]. Therefore, knowledge of the time intervals to first childbirth after HIV diagnosis regarded as the first birth interval after HIV diagnosis (FBI_HIV) and its determinants are crucial to reproductive health care programming.

Previous studies have examined incidence and/or determinants of fertility experience after HIV diagnosis. For instance, studies conducted in Canada and Spain respectively have reported that about one-quarter and two-fifth of women were pregnant after HIV diagnosis [8, 9]. In Uganda, a sub-Saharan Africa country, about one-third of WLWH were pregnant within three years of ART initiation [11]. Socio-economic and demographic factors that could influence pregnancy or birth after HIV diagnosis include age at diagnosis [8, 15], duration since HIV diagnosis [6, 8], marital status [16], working status and parity [17]. With a total fertility rate of 5.3 births per woman [18] in Nigeria, and barely 50% ART access among people living with HIV, information on FBI_HIV is rare.

In the light of this, there is a need to explore the interval between HIV diagnosis and succeeding childbirth in a high fertility setting like Nigeria. Knowledge of FBI_HIV and its determinants can serve as evidence-based information for maternal and child health programmes and policy decision. The main goal of this study is therefore to assess the timing of first birth after HIV diagnosis among women of childbearing age in Ibadan, Nigeria and identify its associated factors. To address these objectives, a semi-parametric model for event history analysis was employed. This is necessary for objective and unbiased inferences. By and large, this would provide health officials with a better understanding of the attitudes of these women regarding the impact of HIV on childbearing and the factors associated with their reproductive decision-making.

Methods

Study design and setting

A cross-sectional survey on childbearing progression and proximate determinants of fertility among WLWH in Ibadan was conducted between November and December 2015. Data was collected on full birth history for each woman which include birth order, sex, birthdate, time of birth (before or after HIV diagnosis), survival status (dead or alive), current age if alive, age at death (if dead) and preceding birth interval.

The study was conducted at the ART clinic of the University College Hospital (UCH). After information about the study was provided to all clinic attendees, nurses/counsellors referred the eligible consenting women to participate after every routine patients’ education session. Over the two months period of data collection, an average of 25 participants was required on each clinic day. At every clinic visit, simple random sampling technique was used to select eligible consenting women. Sampling frame was the daily attendance register kept at the Record section of the clinic. Secret ballot-papers labelled “Yes” or “No” were prepared for the eligible women who registered on a clinic day. Of the total ballots, there were only 25 “Yes”. Anyone who selected a “Yes” was enrolled to participate in the study after written informed consent was obtained.

Data were collected using pre-tested structured questionnaire. The interviewers who were female research assistants and postgraduate students in the College of Medicine were trained at a one-day workshop. During the training, they received general orientation about the study objectives, interviewing skills and health research ethics. Each question item was explained as well as how to record the responses. Data collection instrument (questionnaire) contained sections on socio-demographic characteristics, reproductive history, contraceptive knowledge and use, marital relationship and HIV care/treatment.

Study population and variables

The study sample consisted of 933 consented women aged 18–49 years who had at least a childbirth before or after HIV diagnosis, enrolled for treatment (on ART) and care (not on ART) and supplied all required dates for relevant events for at least 12 months as at the time of the survey. All critically ill clients who were not well enough to provide responses were excluded.

Outcome variable

The main outcome of interest in this study was FBI_HIV. It was estimated as number of years elapsed between date of HIV diagnosis and date of first birth thereafter. For proper event history analysis, women who did not have a childbirth after HIV diagnosis were right-censored and their time to event estimated as interval between date of HIV diagnosis and date of data collection.

Explanatory variables

The explanatory variables considered for this study were women’s socio-demographic characteristics (age at diagnosis, ethnicity, religion, education, employment and number of children at HIV diagnosis), marital profile (marital status at diagnosis, partner’s education, partner’s employment, desire more children and family setting) and HIV care profile (ART duration, status disclosure to partner and partner’s HIV status). Age at diagnosis was categorised into <25, 25–34 and ≥35 years; number of children at diagnosis: 0, 1–2 and ≥3; ART duration: <4, 4–7 and ≥8 years; marital status at diagnosis: cohabiting before diagnosis and cohabiting after diagnosis.

Data analysis

Survival analysis methods were employed to estimate the rate and determinants of FBI_HIV. Number of years elapsed between date of HIV diagnosis and first birth thereafter was the “failure time” for women who had had first birth after HIV diagnosis. Kaplan-Meier survival method and log-rank test respectively was used to describe women’s FBI_HIV and examine its association with each of the covariates. Semi-parametric extended Cox proportional hazard regression model was thereafter applied to identify determinants of FBI_HIV.

Kaplan-Meier survival method

It is a nonparametric method that estimates survival function or probability of surviving beyond a given time t. Suppose T is a random variable denoting survival time of a woman having her first childbirth after HIV diagnosis beyond a specific time t, then the probability of T is the survival function {S(t)} expressed as a function of a cumulative function {F(t)}:

S(t)=tf(y)dy=P(T>t)=1F(t) (1)
F(t)=0tf(y)dy=P(T<t) (2)

The F(t) is the cumulative probability that a woman has her first childbirth after HIV diagnosis before time t. Meanwhile, f(t) is the probability density function of the survival time T, defined as the probability that a woman has her first childbirth after HIV diagnosis per unit time in a short interval expressed as:

f(t)=limt0{P(tT<t+t)t} (3)

Equivalently, S(t) could be expressed as a hazard function {H(t)}:

log[S(t)]=H(t)S(t)=eH(t) (4)

Such that the conditional probability of experiencing first childbirth after HIV diagnosis within a short time interval (t, t + Δt) having survived till time t could be expressed as:

h(t)=limt0{P(tTt+t|T>t)t} (5)

If ni is the number of women who were exposed to the risk of having first birth after HIV diagnosis, censored women inclusive, before ith survival time (ti) and li is the number of women who had first birth after HIV diagnosis at ti, then Eq (6) below estimates the survival functions.

s(t)=i=1m{nilini}tm<t<tm+1;s(t)=1ift<t1 (6)

where m is the number of different failure times (i.e., experiencing first birth after HIV diagnosis)

The Kaplan-Meier estimate of the survivor function above gives a descriptive summary of FBI_HIV including the median survival time.

Cox proportional hazards model

The semi-parametric Cox proportional hazard regression model is expressed as:

h(tt)=h0(t)eb1x1i+b2x2i++bpxpi (7)

and

log{h(ti)h0(t)}=b1x1i+b2x2i++bpxpi (8)

where bj is the jth coefficient of the predictor variable Xj, p is the number of independent variables, while h0(t) is the baseline hazard function.

An important assumption for the Cox regression model is the proportional hazard assumption which requires the hazard ratio (HR) to be constant over time. This was investigated graphically; parallel curves indicate proportionality. Also, Schoenfeld residuals test was conducted in which p < 0.05 implies the violation of the proportional hazard assumption. Even though using the two approaches simultaneously is recommended, Schoenfeld residual test is more objective than the log-log survival plot [19, 20].

Commonly used non-proportional hazard models are stratified and extended Cox regression models [19, 21]. Even though stratified cox model is equally effective, effect of the variable used to stratify would not be obtained. Hence, extended Cox regression which suggests non-proportional hazards over time was employed in this study. It models time-dependent variable(s) interaction with time. The model is expressed as:

h(ti,x(t))=h0(t)exp{(b1x1i++bp1xp1i)+(a1x1ig1(t)++ap2xp2igp2(t))} (9)

and

log{h(ti,x(t))h0(t)}=(b1x1i++bp1xp1i)+(a1x1ig1(t)++ap2xp2igp2(t)) (10)

where

p = p1+p2 predictors such that p2 predictor(s) interact with time since proportional assumption fails

aj = jth overall effect of Xj(t) = Xj × gj(t) (time dependent predictor(s)) such that its positive value indicates increase in hazard as time-to-event increases; otherwise, it decreases

gj(t)={0,PHassumptionmett,interactionXjtforjthvariableIn(t),interactionXjIn(t)forjthvariableheavisidefunction,contantHRfordifferenttimeintervalstimefunctionofvariable.

The coefficient bj indicates the changes in the expected duration of FBI_HIV for every unit change in the jth predictor. The exponentials of the coefficients suggest the tendency of a woman exposure to having a first childbirth after HIV diagnosis; thus, HR >1 indicates higher exposure, HR < 1 lower exposure and HR = 1 equally likely exposure. All significant variables (p≤0.25) emanated from the log-rank test including clinically important variable(s) were included in the extended Cox regression model [22]. All analyses were conducted at 5% level of significance using STATA 14 SE (StataCorp LP, College Station, USA).

Ethical approval

The University of Ibadan/University College Hospital Instituional Review committee approved the survey protocol with approval number (UI/EC/15/0230). Participants gave informed consent and were informed of their freedom to withdraw from interview at any point, prior to data collection. Every tenet of Helsinki declaration and other ethical requirements were strictly complied with throughout the study. No identifying information was collected from participants and study questionnaires were accessible to only investigators and authorised research staff.

Results

Women’s characteristics

Table 1 presents the women descriptive statistics, median survival time and log-rank test of survival curves equality. The mean age of the women was 38.1(±SD = 6.1) years (though not displayed in Table 1). Women aged <25 (12.2%) and 25–34 years (53.9%) constituted the least and the highest proportion of women studied respectively. Most women had secondary education (47.5%) and desired more children (53.6%). The result also showed 37.2% of the women had been on ART for 4–7 years, while 48.0% had HIV-negative partners. Majority of the women were Yoruba (80.5%), employed (90.4%), had employed partner (85.1%), disclosed status to partner (86.7%), and had at least a living child at diagnosis (77.8%).

Table 1. Characteristics of women aged 18–49 years diagnosed of HIV in Ibadan, Nigeria.

Characteristic Total at risk Had first birth (n = 413) MF p-value^
n % % years
Age at diagnosis (years) <0.001***
<25 114 12.2 67.5 4
25–34 503 53.9 55.9 5
≥35 316 33.9 17.4 na
Education 0.001***
None 63 6.8 25.4 na
Primary 195 20.9 37.9 14
Secondary 443 47.5 44.7 7
Higher 232 24.9 53.9 5
Employment 0.027**
Not working 90 9.6 54.4 4
Working 843 90.4 43.2 8
Ethnicity 0.001***
Non-Yoruba 182 19.5 53.3 5
Yoruba 751 80.5 42.1 9
Religion 0.348
Christian 567 60.8 45.9 7
Islam 366 39.2 41.8 9
No of children at diagnosis <0.001***
None 207 22.2 73.4 3
1–2 444 47.6 46.2 6
≥3 282 30.2 19.9 14
Marital status at diagnosis+ <0.001***
Cohabiting after diagnosis 105 11.4 74.3 4
Cohabiting before diagnosis 819 88.6 40.4 10
Partner education+ 0.021**
None 38 4.1 21.1 na
Primary 99 10.6 39.4 na
Secondary 444 47.6 43.9 7
Higher 337 36.1 49.6 6
Partner employment <0.001***
Working 794 85.1 47.0 7
Not working 139 14.9 28.8 na
Desire for more children 0.258*
No more 433 46.4 42.0 9
Desired 500 53.6 46.2 7
Family setting+ <0.001***
Monogamy 596 65.6 51.0 6
Polygamy 312 34.4 32.1 na
ART use duration (years) 0.169*
<4 324 34.7 36.4 5
4–7 347 37.2 45.8 8
≥8 262 28.1 51.9 9
Status disclosure to partner 0.024**
Non-disclosure 124 13.3 50.8 5
Disclosure 809 86.7 43.3 9
Partner HIV status 0.002***
Don’t know 228 24.4 32.0 17
Positive 257 27.5 44.7 8
Negative 448 48.0 50.2 6
Total 933 44.3 8

* p≤.25

** p < .05

***p < .001

^ based on log-rank test

+ missing not reported; n–number of women; MF—Median FBI_HIV; na–MF cannot be computed owing to category’s low percentage of women who had first birth after HIV diagnosis

Of 933 women, 413 (44.3%) had had first birth after being diagnosed of HIV as at the survey date. Women who were cohabiting before being diagnosed (10 years) and had primary education (14 years), ≥3 children at diagnosis (14 years) or no knowledge of partner’s HIV status (17 years) delayed the first birth in at least 10 years after HIV diagnosis. Nearly all the selected variables had significant (p≤0.25) differences in their respective category’s survival curves except for religion. For instance, a significantly higher percentage of women aged <25 years (67.5%) and those who had been using ART for at least 8 years prior to the date of interview (51.9%), had no child before HIV diagnosis (73.4%) or cohabited prior to HIV diagnosis (74.3%) gave birth after HIV diagnosis. The median time to first birth after HIV diagnosis was 8 years (Table 1). This is also revealed in Fig 1, which demonstrates the probabilities of the risk of having a first birth after the HIV diagnosis and the survival rate.

Fig 1. Overall survival and hazard function of FBI_HIV.

Fig 1

The probability plot displaying the cumulative survival curve and the risk of having a first birth after HIV diagnosis.

Investigation of proportional hazard assumption

Asides the Schoenfeld test, the graphical assessment of the proportional hazard assumption is shown in Fig 2. The outcome showed that proportional hazard assumption failed (global test: p = 0.015). Further investigation revealed that age at diagnosis (p = 0.014) violated the proportional hazard assumption. Extended cox regression was considered for further analysis as it suffices in handling non-proportional hazards.

Fig 2. Log-log survival plot.

Fig 2

This plot shows a graphical examination of the proportional hazard assumption.

Predictors of time to first birth after HIV diagnosis

The outcomes of the extended Cox regression model are presented in Table 2. Age at diagnosis (time-varying variable), ART use duration, desire for more children, number of children at diagnosis, partner’s education and knowledge of partner’s HIV status were significantly associated with FBI_HIV. Women who desired for more children after HIV diagnosis (HR = 0.63; CI: 0.51–0.78; p<0.001) had a 37% reduced likelihood of shortening FBI_HIV compared with those who want no more. Increasing years of ART use was associated with a lower hazard of shortened FBI_HIV. For instance, women who had used ART for 4–7 (HR = 0.74; CI: 0.59–0.92; p = 0.006) and ≥ 8 (aHR = 0.78; CI: 0.44–0.70; p = 0.034) years were more likely to delay first childbirth after HIV diagnosis compared with their counterpart with a short duration of ART use. The possibility of a first birth after being diagnosed of HIV declined as number of children at diagnosis increased. Women who had 1–2 (HR = 0.55; CI: 0.44–0.70; p<0.001) and >2 (HR = 0.24; CI: 0.17–0.35; p<0.001) children at diagnosis respectively had 45% and 76% reduced risks of having first birth relative to women with no surviving child at diagnosis. Interestingly, women whose partners had primary and secondary education respectively were about 2.3 times more likely of having first birth after HIV diagnosis compared to those whose partners had no formal education. Similarly, women who had the knowledge of their partners’ HIV-positive status (HR = 1.42; CI: 1.04–1.93; p<0.027) were about 42% more likely to have first birth after HIV diagnosis relative to those who did not know their partners’ HIV status. Although older age was insignificantly associated with higher likelihood of having a first birth at the time of diagnosis, older age lengthened FBI_HIV subsequently. Such that the hazard of having a first birth after HIV diagnosis was about 35% less likely among women aged ≥35 years (HR = 0.64, CI: 0.51–0.80; p<0.001) compared to those aged <25 years.

Table 2. Effect of selected characteristics on time to first birth after HIV diagnosis among women aged 18–49 years in Ibadan, Nigeria.

Characteristics (n = 903) HR 95% CI p-value
Age at diagnosis
<25 Ref
25–34 1.32 0.83,2.10 0.240
> = 35 1.14 0.57,2.27 0.715
Educational level
None Ref
Primary 1.42 0.81,2.51 0.225
Secondary 1.58 0.91,2.74 0.104
Higher 1.63 0.91,2.92 0.099
Employment Status
Not working Ref
Working 0.88 0.64,1.21 0.433
Ethnicity
Non-Yoruba Ref
Yoruba 0.84 0.66,1.07 0.155
No of children at diagnosis (Q505_b) Q505N
None Ref
1–2 0.55 0.44,0.70 0.000***
> = 3 0.24 0.17,0.35 0.000***
Marital status at diagnosis (marital_b)
Cohabiting before diagnosis Ref
Cohabiting after diagnosis 0.97 0.71,1.33 0.853
Partner education
None Ref
Primary 2.35 1.08,5.13 0.031*
Secondary 2.30 1.11,4.79 0.026*
Higher 1.87 0.89,3.94 0.098
Partner employment (Q407_b) (Q107)
Not working Ref
Working 1.37 0.95,1.98 0.091
Family type
Monogamy Ref
Polygamy 0.83 0.65,1.06 0.132
Desire for more children
No more Ref
desired 0.63 0.51,0.78 0.000***
ART use duration
<4 Ref
4–7 0.74 0.59,0.92 0.006**
≥8 0.57 0.40,0.81 0.002**
Status disclosure to partner
Non-disclosed Ref
Disclosed 0.94 0.71,1.24 0.658
Partner’s HIV status
Don’t know Ref
Positive 1.42 1.04,1.93 0.027*
Negative 1.22 0.92,1.63 0.173
Age at diagnosis*t
<25*time Ref
25–34*time 0.88 0.79,0.98 0.020*
≥35*time 0.64 0.51,0.80 0.000***

* p < .05

** p < .01

***p < .001; HR–adjusted hazard ratio; CI–Confidence interval; Ref–reference category

Discussion

This study was conducted to examine the timing of first birth after HIV diagnosis among women of reproductive age who attend ART clinic in Ibadan Nigeria. Despite most women having at least one child at the time of HIV diagnosis, nearly half had first birth after HIV diagnosis. This result buttresses the importance of motherhood as a means of coping with HIV diagnosis [10], and the need to integrate reproductive counselling into HIV treatments and care in Nigeria. Although the available literature reported one-quarter of women being pregnant after HIV diagnosis in Canada [9], the percentage of women having at least a child after HIV diagnosis is high in Nigeria. By implication, it is also higher than 39% found in a cross-sectional study conducted among women aged 18–49 years in Spain [8].

Of note, our finding showed that the median first birth interval after HIV diagnosis (8 years) was long. This interval is higher compared to the findings of studies conducted in Brazil, Spain and Uganda which reported 2, ≤ 2 and 3.8 years interval between HIV diagnosis and the first pregnancy, respectively [8, 11, 23]. The birth interval is a bit longer among the women studied compared to the median birth interval of about 2.6 years among the general population of women of reproductive age in Nigeria [24]. This study revealed that FBI_HIV in Nigeria is influenced by age at diagnosis, ART use duration, desire for more children, increased in number of children at diagnosis, and having educated partner or knowledge of partner’s HIV status.

Interestingly, despite the insignificant time-varying effect of age at diagnosis, the likelihood of having a first birth after HIV diagnosis significantly decreased with age. This result aligns with an earlier study [11] conducted in Uganda among HIV-positive women of childbearing age which concluded that being younger is significantly associated with pregnancy risk. Of course, women are more likely to delay first childbirth till their advanced reproductive age as observed in this study; this is consistent with the finding of a study in Colombia [15]. This may suggest an urgent sensitisation and advocacy on the related pros and cons of postponing childbirth till older childbearing age among WLHW.

While Kaida and colleagues [11] opined that disclosure of HIV status to partner is significantly associated with the risks of being pregnant after diagnosis, our study suggested that a knowledge of partner’s HIV-positive status significantly shortened the interval. This may likely suggest a concluded agreement between the women and their respective partners to increasingly give birth early after HIV diagnosis, perhaps due to enrolment for ART treatment and care. This has an implication for the women childbearing planning considering the vital role of partners in fertility decision-makings. However, nearly three-quarter of women confirmed either partner’s HIV-unknown or HIV-negative status as observed in this study; this is an indication of partners at-risk population for HIV infection. This therefore calls for an all-inclusive reproductive healthcare and conception counselling programmes for WLWH and their respective partners to be integrated into HIV care programmes [15].

It is also worth noting that the tendency of women to have first birth after HIV diagnosis was higher among those whose partners are educated. Contrary to the belief that higher education improves women’s social and economic status and offers women access to non-childbearing activities, having educated partner stimulated childbirth after HIV diagnosis. Other empirical literature has established the role of partner decision-making in women reproductive process which could be linked to the knowledge that ART could prevent either partner or their children from being HIV-positive [25]. This, coupled with the idea of showcasing reproductive prowess, may motivate the considerable increase in number of childbirth after HIV diagnosis [6, 8, 17].

Furthermore, increasing years of ART use or desire for more children increases the FBI_HIV in consistent with similar studies in other settings [6, 7]. This is not surprising as the association between ART use duration and fertility desire has been reported in literature [7]. This may be hinged on the believe that the longer the duration on ART, the higher the improved quality of life and consequently the more likely to raise children free from HIV infection. Another possible reason may be associated with the tendency of the women to consolidate their relationship by having more children as most WLWH in relationships usually have partners who are yet to father a child [5, 6].

In addition, increased number of children at diagnosis had a protective effect against shortened FBI_HIV as women were less likely to have children either in the short or long term. This finding corroborates previous studies in other contexts [2628]. As women attain their desired family size, the likelihood to desire or have additional child may decrease or cease altogether [29].

Limitations of the study

This study has its limitations. With a cross-sectional design, in-depth analysis of temporal relationship between HIV diagnosis and childbearing transitions could not be carried out. Besides, self-reported data collected retrospectively with no means of verification may influence recall bias. This, however, has been overcome by the usage of carefully designed questionnaire and trained interviewers to reduce perceived bias to the barest minimum.

Conclusions

In conclusion, information on fertility timing after HIV diagnosis is necessary for care and management of people living with HIV. The percentage of women who had first birth after HIV diagnosis is considerable with a high median time to first birth after HV diagnosis. Several factors including advanced women age at diagnosis, duration of ART use, desire for more children and number of children at HIV diagnosis have been identified as risk factors of women’s first birth interval after HIV diagnosis. Other factors include having partners who were HIV-positive or attained formal education. These identified factors should be integrated into HIV care program design and implementation.

Acknowledgments

We appreciate the cooperation of study participants and staff members at the UCH Antiretroviral Clinic, Ibadan.

Data Availability

Data cannot be shared publicly because of ethics policy at University of Ibadan. Data are available from the UI/UCH Institutional Data Access / Ethics Committee (contact via uiuchec@gmail.com) for researchers who meet the criteria for access to confidential data

Funding Statement

The author(s) received no specific funding for this work.

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Decision Letter 0

Kannan Navaneetham

2 Jul 2020

PONE-D-20-04600

Semi-parametric model for time to first birth after HIV diagnosis among women in South-West, Nigeria

PLOS ONE

Dear Dr. Afolabi,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

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If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

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We look forward to receiving your revised manuscript.

Kind regards,

Kannan Navaneetham, PhD

Academic Editor

PLOS ONE

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'The project from which this data was extracted was supported

by the Medical Education Partnership Initiative in Nigeria (MEPIN) project funded by

Fogarty International Centre, Office of AIDS Research, and the National Human Genome

Research Institute of the National Institute of Health, the Health Resources and Services

Administration (HRSA) and the Office of the U.S. Global AIDS Coordinator under Award

Number R24TW008878.

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Additional Editor Comments (if provided):

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Partly

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: No

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: No

Reviewer #2: No

**********

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: No

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Comments

1. The title should be modified as per the study objectives.

2. The abstract is too long (particularly, result part). Try to make it short and precise.

3. Some edition is needed. (eg: line 28, 32 pronoun “we” is wrongly used).

4. How much of the data were 'valid' and what was the level of missingness for the variables of interest that you used?

5. Be consistent in your references citation (eg. Line 74-line 78 different reference citation )

6. On Line 124: you have stated that “women aged 18-49 years who had had at least a child-birth…. ” were considered in the study. From line 129-30 it has been stated that “For proper event history analysis, women who did not have a child birth after HIV diagnosis were censored…. ” which contradicts the former statement. Take a look.

7. Line 211: why you need to have exponential distribution test?

8. Line 245: Employment status (p=0.049) violated the proportional hazard assumption but the graph for employment status (Fig 2) is parallel which implied that PH assumption is not violated. How could it be?

9. Table 2 on page 13: It has been identified that Cox PH model is not appropriate since PH assumption is violated for some explanatory variables. Once the violation of PH assumption is detected, no need to keep cox PH model for comparison purpose with extended cox model. It is better to consider only the extended model and interpret the result. Model comparison should be made (using AIC, BIC, ) only between appropriate models for the particular data.

10. Interpretation of HR is not clear.

11. Be consistent when you write the response variable (first birth interval after diagnosis or time to first birth after diagnosis). Line 337 “first birth after HIV diagnosis” is not good expression.

12. Inclusion exclusion criteria are not clearly stated.

13. Limitation should be separated from discussion.

Reviewer #2: Generally the authors need to check on grammatical mistakes that abound in the manuscript. Some have been highlighted.

Data Analysis

Kaplan Meier.

The notations and definitions are misleading. The authors use the random variable T to denote a woman who had her FBI_HIV beyond t time. Normally T denotes the future lifetime random variable of an individual aged 0(newborn) .In this context, T could be time to first birth after HIV diagnosis, so that s(t0 is the probability of birth after t years.

Equation 2 is wrong, the integral should be from 0 to t and not 1.

Following the author’s arguments, the probable definition of f(t) is the probability that a woman has a child at time t.

The equations are poorly written, kindly use latex, Microsoft equation etc.

The author is also silent on the censoring mechanism assumed in the data.

Line 160: Mixed up notations: What does t_i represent? Survival times, or failure times/birth times. There is also a general mix up under this heading.

COX PH

Line 190, 191: Not clear

Women Characteristics

Although the author states that table 1 displays among others the Kaplan Meier survival estimates, I have been unable to see the Kaplan Meier survival estimates.

Results and discussions

It would be of great value for the authors to outline how they selected the covariates. What feature selection techniques were employed?

Important features like use of ART and status of the partner have been left out.

**********

6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: Yes: Ayele Gebeyehu Chernet

Reviewer #2: Yes: Elphas Okango

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

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Decision Letter 1

Kannan Navaneetham

16 Sep 2020

PONE-D-20-04600R1

Semi-parametric model for timing of first childbirth after HIV diagnosis among women of childbearing age in Ibadan, Nigeria

PLOS ONE

Dear Dr. Afolabi,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Please submit your revised manuscript by Oct 31 2020 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

  • A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

  • A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

  • An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols

We look forward to receiving your revised manuscript.

Kind regards,

Kannan Navaneetham, PhD

Academic Editor

PLOS ONE

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #2: (No Response)

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #2: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #2: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #2: No

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #2: No

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #2: The authors have made a great improvement on the manuscript, however there are still some issues:

There still exists some grammatical mistakes e.g line 25, 61, 213, 237 etc.

Line 85: Which data is the author talking about?

Line 170: use math type, Microsoft equation, latex, or r markdown to type equations/ mathematical symbols.

Line 192. The coefficients b_js are not used to indicate statistical significance, but the strength and direction of relationship.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #2: No

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

Decision Letter 2

Kannan Navaneetham

23 Sep 2020

Semi-parametric model for timing of first childbirth after HIV diagnosis among women of childbearing age in Ibadan, Nigeria

PONE-D-20-04600R2

Dear Dr. Afolabi,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Kannan Navaneetham, PhD

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Acceptance letter

Kannan Navaneetham

28 Sep 2020

PONE-D-20-04600R2

Semi-parametric model for timing of first childbirth after HIV diagnosis among women of childbearing age in Ibadan, Nigeria

Dear Dr. Afolabi:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Professor Kannan Navaneetham

Academic Editor

PLOS ONE

Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    Attachment

    Submitted filename: Response to Reviewers.docx

    Attachment

    Submitted filename: Response to Reviewers_R2edit.pdf

    Data Availability Statement

    Data cannot be shared publicly because of ethics policy at University of Ibadan. Data are available from the UI/UCH Institutional Data Access / Ethics Committee (contact via uiuchec@gmail.com) for researchers who meet the criteria for access to confidential data


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