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Article

Understanding Pregnancy Intentions among Black Women Living with HIV in Two North American Cities and One African City

by
Egbe B. Etowa
1,2,*,
Ruby Edet
3,
Andrea Willett
4,
Manal Fseifes
4,
Faith Diorgu
5,
Jean Hannan
6,
J. Craig Phillips
4,
Sanni Yaya
7,
Aniekan Etokidem
8 and
Josephine Etowa
4
1
Daphne Cockwell School of Nursing, Toronto Metropolitan University, Toronto, ON M5B 2K3, Canada
2
Ontario HIV Treatment Network (OHTN), Toronto, ON M4T 1X3, Canada
3
Canadians of African Descent Health Organisation, Ottawa, ON K1H 8M5, Canada
4
School of Nursing, University of Ottawa, Ottawa, ON K1H 8M5, Canada
5
School of Nursing, University of Port Harcourt, PMB 5323 Choba, Port Harcourt 500004, Rivers State, Nigeria
6
Nicole Wertheim College of Nursing & Health Sciences, Florida International University, Miami, FL 33199, USA
7
School of International Development and Global Studies, University of Ottawa, Ottawa, ON K1N 6N5, Canada
8
Department of Community Medicine, Faculty of Medicine, University of Calabar, Calabar 540271, Cross River State, Nigeria
*
Author to whom correspondence should be addressed.
Women 2023, 3(2), 310-321; https://doi.org/10.3390/women3020023
Submission received: 22 April 2023 / Revised: 16 May 2023 / Accepted: 24 May 2023 / Published: 6 June 2023
Browse Figure
Versions Notes

Abstract

:
Despite increased access to and improvements in contraceptives, unintended pregnancy continues to be a problem globally and is associated with adverse outcomes for mothers and infants. This paper seeks to unravel the mediators of intended versus unintended pregnancies among Black women living with HIV. The paper draws on survey data from a broader multi-country mixed methods study that used a community-based participatory research approach to investigate the psychosocial experiences of Black mothers living with HIV. The study participants were Black mothers living with HIV drawn through venue-based sampling from Ottawa, Canada (n = 89), Port Harcourt, Nigeria (n = 400), and Miami, Florida, United States (n = 201). We used Hierarchical Binary Logistic Regression Modelling (HBLM) to estimate the independent associations of pregnancy intention (intended versus unintended) with blocks of predictor variables (sociodemographic, sociocultural, and psychosocial predictors) at alpha level of 0.5. Specifically, 44.2%, 67.3%, and 17.7% of the women had unintended pregnancies in Ottawa, Miami, and Port Harcourt, respectively. There were important results from the HBLM. The odds of intended relative to unintended pregnancies were (i) reduced in larger households (OR = 0.56, 95% CI = 0.36/0.87), but increased with employment (OR = 7.84, 95% CI = 1.52/40.54) and HIV knowledge (OR = 3.13, 95% CI = 1.42/6.90) in Ottawa; (ii) reduced with age (OR = 0.93, 95% CI = 0.88/0.98), but increased with marriage (OR = 2.90, 95% CI = 1.43/5.88) and social support (pregnancy (OR = 3.77, 95% CI = 1.98/7.19) in Port Harcourt; (iii) reduced with social support (OR = 0.95, 95% CI = 0.91/1.00) but increased with HIV status disclosure (OR = 1.73, 95% CI = 1.01/2.97) and the influence of specific referent (OR = 1.68, 95% CI = 1.13/2.52) in Miami-FL. The incidence of unintended pregnancy is more prevalent among Black women living with HIV in the North American cities relative to the African city. Also, unique combinations of sociodemographic, sociocultural, and psychosocial factors influence pregnancy intention in each city. This implies that policy and practices to address reproductive health needs of WLHIV must consider these contextual issues.

1. Introduction

Pregnancy intentions may be classified into two main categories: unintended and intended. An unintended pregnancy is defined as either unwanted or mistimed [1]. By contrast, intended pregnancies are described as “those that happened at the right time or later than desired due to infertility or difficulties conceiving” [2]. Approximately 74 million women living in low and middle-income countries have unintended pregnancies annually [3]. Overall, women in low-income countries are almost three times more likely to experience unintended pregnancy than women in high-income countries. The rate of unintended pregnancy is 0.035% among women aged 15–49 years in Europe and North America, and 0.091% among women in sub-Saharan Africa [4]. In the United States in 2011, 45% of pregnancies were unintended and were far more likely to occur among Black and Hispanic people compared to White people [5].
Among Women Living with HIV (WLHIV) in Canada, the unintended pregnancy rate was 60.8% [6], relative to the national rate of 27% reported in 2009 [7]. Studies in Africa show that unintended pregnancy rates among WLHIV varied between a low of 15% in Nigeria (Bankole et al., 2014) to a high of 62% in South Africa [8]. In line with this, other studies have shown that unintended pregnancy is more common among WLHIV [9,10]. Furthermore, a United States study showed that African American women living with HIV were more likely to have unintended pregnancies than other women [11]. In Canada, 60% of WLHIV never discussed their pregnancy intentions with their healthcare provider due to fear of stigma. Moreover, low contraceptive use was found among WLHIV not intending to get pregnant compared to other women groups.
Unintended pregnancies constitute a global concern, as statistics show that they result in about 25 million unsafe abortions and 47,000 maternal deaths globally [3]. A United States study in 1994 found that about 50% of pregnancies were unintended, and 50% of unintended pregnancies culminate in abortion [12,13]. In jurisdictions where abortion is criminalised, unintended pregnancies may increase maternal morbidity and mortality [14,15]. Studies have also shown negative consequences of unintended pregnancies including non-detection of early pregnancy [16], poor prenatal care, lower breast-feeding intentions, low birthweight [17], greater risk of social, mental, and general health challenges of children born through unwanted pregnancies, and poor school performance [18]. Babies born via unintended pregnancy are more prone to mortality within the first six months of life from being abused, and to developmental problems. Unintended pregnancy predisposes women to psychosocial distress, depression, spousal violence, and loss of marital relationships [13].
Unintended pregnancy among women living with HIV yields additional, but unique, burdens. For example, unintended pregnancy has been associated with poor treatment outcomes among women living with HIV who initiate antiretroviral treatment during pregnancy [19]. Unintended pregnancy has been associated with vertical transmission of HIV [20]. Finally, evidence suggest that unintended pregnancy increases the psychosocial and economic difficulties experienced by women living with HIV [21].
While unintended pregnancies constitute a significant global concern among all groups of women, including WLHIV, several socioeconomic and psychosocial factors remain implicated in their proliferation. For example, a pregnancy intention is influenced by a woman’s age, marital relationship, medical conditions, familial and social pressures, exposure to relationship abuse, emotional reactions, and prenatal diagnostic procedures [22,23,24,25,26]. Unintended pregnancy among WLHIV has been significantly associated with low socioeconomic status [27] and intimate partner violence [28]. In addition, changing pregnancy intention has been linked with gravidity [29] and parity [26,29,30,31,32] among WLHIV. Although younger-aged WLHIV have been found to have greater intention to become pregnant [33,34,35], they are also more prone to ultimately having mistimed (unintended) pregnancies [32,36] due to their demotivation to discuss their pregnancy intentions with healthcare professionals for fear of HIV-related stigma and discrimination [37,38,39,40,41]. Moreover, internalized HIV stigma and childbearing stigma among WLHIV are key barriers to communicating with healthcare providers about pregnancy intentions [39]. Yet pregnancy intentions can be positively influenced to a significant extent by social support, including health professionals’ advice [42,43].
In this study we explored pregnancy intentions and their socioeconomic and psychosocial determinants among Black women living with HIV in Ottawa, Canada; Miami, Florida, USA, and Port Harcourt, Nigeria. The study seeks to provide a sound understanding of pregnancy intentions among Black WLHIV and to compare experiences among non-migrants in the Global South to immigrant women in the Global North. Such an understanding aims to promote the right policy dialogues and programming that will guide future pregnancy intentions at individual, interpersonal, community, and population levels. This aim is premised on the fact that connecting with the right information through policy and the healthcare system has been recognized as an important step towards addressing reproductive decisions, preventing issues related to unintended pregnancies, and HIV transmission. Moreover, the separate city analysis provides useful transference of lessons learnt from one city to another, or from Black immigrant to non-migrant women or vice versa, in terms of policy transformation.

2. Methods

This paper draws cross-sectional survey data from a broader multi-country mixed methods study that used a community-based participatory research approach to investigate the health experiences of Black mothers living with HIV. The guiding principles and methods of the study have been explicated [44,45,46,47]. The paper describes pregnancy intentions (intended versus unintended) among Black women living with HIV in three countries. It also explored the sociodemographic, sociocultural, and psychosocial factors associated with intended relative to unintended pregnancy in each of the countries. Specific datasets used in the analyses were: Ottawa, Canada (n = 89); Port Harcourt, Nigeria (n = 400), and Miami, Florida, United States (n = 201).
The datasets used in the analyses were the predicted variable (pregnancy intention) and two categories of predictor variables (sociocultural and psychosocial factors) while controlling for the sociodemographic variables. To measure pregnancy intention, participants were asked, “At the time you became pregnant while living with HIV, had you planned to become pregnant?” Responses were dichotomized as follows: “yes” (intended pregnancy) = 1, “no” (unintended pregnancy) = 0. The list of sociodemographic variables controlled for in the final model after multiple iterations were age, marital status, household size, mean age of children born after being HIV positive, educational experience, and employment status. Distinct measures of these variables are provided in Table 2 of the results section.
The sociocultural factors include disclosure of HIV status (disclosed to spouse only = 1, disclosed to spouse and other family members = 2, did not disclose to anyone = 0). Motherhood experience was measured with the Being a Mother Psychometric Scale [46,48]. The Being a Mother scale consist of 13 items that highlights the mother’s experience of herself as an adult with offspring, her experience of her child, and her emotional closeness with her child. Social support was measured using seven items adapted from the Duke-UNC Functional Social Support Questionnaire [44,49]. The contents of the seven-item scale elicit information about receiving care, being listened to, being socially connected, receiving useful advice, and being helped when sick. Other sociocultural factors included support on infant feeding decisions i.e., if the women received complimentary guidance on how to feed their infants when living with HIV (yes = 1, no = 0). We also measured the influence of specific referents (ISR) using an adapted scale [47,50]. The adapted scale assessed the women’s rating of the wishes of their social network regarding their infant feeding choice, and the women’s motivation to comply with those wishes. The social network in this case included: spouse, family/relatives, cultural setting/community network, and health service providers. The psychosocial factors included HIV knowledge (rating of levels of knowledge about the vertical transmission of HIV (pregnancy, delivery, and breastfeeding). Scores of 0, 1, 2, or 3 were assigned if the participants had knowledge of none, one, two, or all three modes (pregnancy, delivery, and breastfeeding) of vertical transmission of HIV, respectively. Self-rated maternal stress scores were measured on a 10-item Perceived Stress Scale [45,51]. Hypervigilance and HIV-related discrimination were also measured on validated psychometric scales [52,53,54].
The Hierarchical Binary Logistic Regression Modelling (HBLM) was used to estimate the correlation between pregnancy intention and the independent variables (sociodemographic, sociocultural, and psychosocial factors) at an alpha criterion of 0.05. The HLM controlled the effects of sociodemographic variables in Block 1 of the analysis prior to inclusion of Block 2 variables (sociocultural and psychosocial factors). Because of the potential clustering effect of pulling data from different cities in three different countries, we conducted a separate HBLM for each city. Different combinations of the variables were analysed per city, depending on the combination of variables with the best fit and least error estimate using a forward stepwise variables selection approach. In the HBLM for Ottawa, there was significant improvement of the model with inclusion of Block 2 variables as the error estimate (-2LL) dropped to 13.94 from 61.88, and the model became statistically significant (X2 = 28.47, p < 0.001). Port Harcourt HBLM showed a significant improvement of the model with inclusion of Block 2 variables when the error estimate dropped by 27.47 and was statistically significant (X2 = 41.38, p < 0.001). Similarly, HLM for Miami showed significant improvement with addition of Block 2 variables into the model, with its error estimate dropping significantly by 14.68 and becoming statistically significant (X2 = 20.55, p < 0.05).

3. Results

3.1. Sociodemographic Characteristics

Table 1 provides a summary of participants’ sociodemographic characteristics. The average ages of participants were: Ottawa (36.63 years), Port Harcourt (34.67 years), and Miami (34.30 years). Percents of the women married were: Ottawa (33.33%), Port Harcourt (85.21%), and Miami (60.80%). Average years of formal education were: Ottawa (14.34 years), Port Harcourt (12.36 years), and Miami (14.52 years). Percents of the women in employment were: Ottawa (52.90%), Port Harcourt (68.4%) and Miami (23.1%).
Sociocultural factors. On a two-point scale, HIV Status Disclosure scores were: Ottawa (1.30), Port Harcourt (1.67), and Miami (1.39). On average, participants in all three sites had disclosed their HIV status to at least their partner or a family member. Percents of the women who reported receipt of support on their infant feeding decisions were: Ottawa (56.3%), Port Harcourt (83.3%), and Miami (48.90%). On a 45-point scale, the average scores on the Influence of Specific Referents scale were: Ottawa (18.53), Port Harcourt (21.72), and Miami (12.70).
Psychosocial factors. On a 52-point scale, the average motherhood experience scores were: Ottawa (42.99), Port Harcourt (28.58), and Miami (36.66). On a scale of 35 points, average social support scores were: Ottawa (24.77), Port Harcourt (20.72), and Miami (21.9). On a scale of three points, average HIV knowledge scores were: Ottawa (2.4), Port Harcourt (2.65), and Miami (2.4). Heightened Vigilance scores were: Ottawa (12.7), Port Harcourt (10.21), and Miami (7.57), while on a 40-point scale, average maternal stress scores were: Ottawa (16.91), Port Harcourt (22.1), and Miami (21.09). On a 50-point scale, HIV related discrimination scores were: Ottawa (24.84), Port Harcourt (7.28), and Miami (15.55).

3.2. Percent of Mothers with Intended and Unintended Pregnancies

Figure 1 shows percentages of mothers living with HIV who reported intended versus unintended pregnancy following a diagnosis of HIV. Percents of women who reported an unintended pregnancy were: Ottawa (44.2%), Port Harcourt (17.7%), and Miami (67.3%).
Factors associated with pregnancy intention among Black mothers living with HIV in three cities in three countries.
Table 2 presents the results of HBLM to determine sociocultural and psychosocial factors associated with intended pregnancy relative to unintended pregnancy among the women in the three cities, while also showing the effects of the control variables (sociodemographic factors). We report only variables that were significant at 95% a confidence level or higher.
In Ottawa, the odds of intended relative to unintended pregnancy increased with employment (OR = 7.84, p < 0.01, 95% CI = 1.52/40.54) and HIV knowledge (OR = 3.13, 95% CI = 1.42/6.90), but decreased with household size (OR = 0.56, 95% CI = 0.36/0.87). Also, the odds of intended pregnancy (OR = 1.07, p < 0.05, 95% CI = 1.01/1.13) increased with HIV-related discrimination, thereby contradicting the study’s a priori expectation.
In Port Harcourt, the odds of intended relative to unintended pregnancy increased with marriage (OR = 2.9, 95% CI = 1.43/5.88) and social support (OR = 3.77, 95% CI = 1.98/7.19). However, the odds of intended pregnancy decreased with age (OR = 0.93, 95% CI = 0.88/0.98) and motherhood experience (OR = 0.96, p < 0.05, 95% CI = 0.92/0.99), thereby contradicting the study’s a priori expectation.
In Miami, the odds of intended relative to unintended pregnancy increased with Disclosure of HIV Status (OR = 1.73, 95% CI = 1.01/2.97) and the influence of a specific referent score (OR = 1.68, 95% CI = 1.13/2.52). However, the odds of intended relative to unintended pregnancy decreased with functional social support (OR = 0.95, p < 0.05, 95% CI = 0.91/1.00), thereby contradicting the study’s a priori expectation.

4. Discussion

Prevalence of unintended pregnancies. The incidence of unintended pregnancies was much greater among WLHIV in the North American cities, with values ranging from 44.2 to 67.3% in Ottawa and Miami, than those in the African city. This compares to previous statistics showing prevalence rates of 61% among WLHIV in Canada, and a range of 51 to 90% among WHLHIV globally [6,38,55]. A study of 36 countries in Africa showed that prevalence of unintended pregnancy was 30.10%, with values of 41% and 37% in Kenya and Uganda, respectively [56,57,58]. The large disparity in unintended pregnancies between the North American cities and the African city reflects the disproportionate access and utilisation of reproductive health services among immigrant WLHIV as compared to women in Africa. Access and utilisation of healthcare, particularly to reproductive health services, provides avenues for counselling by healthcare professionals that can guide the pregnancy intentions of women including WLHIV. However, the experiences of stigma and discrimination in healthcare facilities lead Black WLHIV to desist from seeking counsel from healthcare providers about their pregnancy intention. The study showed that pregnancy intention was predicted by varied demographic, sociocultural, and psychosocial factors across the three cities, thereby indicating that differing city dynamics influence pregnancy intention. We, therefore, discuss results by city.

4.1. Ottawa, Canada

The findings in Ottawa are supported by other comparative studies, i.e., intended pregnancy correlated with smaller household sizes in other studies [59] and conversely, multiparity correlated with unintended pregnancy among WLHIV [26,60,61]. One valid explanation is that women with large household sizes may spend more time on parenting and domestic tasks, thereby limiting their ability to access family planning information and maternal health services such as contraceptive methods [62]. They may also be inconsistent in the use of contraceptives, under-utilising contraceptives, using emergency contraceptives, having unfavourable side effects of contraceptives, or suffering from partner refusal of contraceptive use. Related to our results in Ottawa that intended pregnancy was predicted by employment status, some other studies in the US, Britain, and Africa found decreased odds of unintended pregnancy with higher socioeconomic status, including education and wealth [5,63,64]. This result is perhaps because employed women may be more conscious about family planning due to work demands, unfavourable maternity leave benefits, and other disincentives. Next, knowledge of modes of HIV transmission among WLHIV in Ottawa increased their odds of pregnancy intention. The result is logical, as knowledge of the fact that HIV is transmissible from mother to child, not only during pregnancy but also during delivery and breastfeeding, leads WLHIV to be intentional about their reproductive decisions. This result underscores the importance of mainstreaming family planning services into HIV care [32]. Finally, we found a contradicting result that experiences of discrimination increase the odds of intended pregnancy, yet we feel that this could be because discrimination breeds negative self-image and personalised stigma, which have been associated with increased intention to get pregnant [65]. WLHIV facing discrimination, who may feel isolated and lack self-worth, may perceive pregnancy and its resulting motherhood experience as a source of personal joy, satisfaction, and motivation to live longer and healthier lives. This may be especially true among women in Black cultures that traditionally value motherhood. Amongst WLHIV in Ontario, Canada, African ethnicity and recent immigration to Canada were significantly correlated with attributing high importance to motherhood, and amongst those reporting that motherhood was important, it was seen as a source of fulfilment and increased self-esteem [66].

4.2. Port Harcourt, Nigeria

First, the odds of intended pregnancy decreased with age among WLHIV. This finding was supported by those of other studies in Africa [29,67,68]. This association could be explained by a greater motivation and perhaps a yet-unfulfilled desire to bear children among younger women. By contrast, in a study of Canadian women, the odds of unintended pregnancy increased among younger WLHIV [6], raising questions about how sociocultural contexts shape norms around adolescent or young motherhood. Secondly, we found comparative results that the odds of intended pregnancy were higher among married WLHIV [6,69]. The results may be linked to higher likelihood of unplanned sexual activity and inconsistent or no contraceptive use among unmarried women. In contrast, a few studies in sub-Saharan Africa showed the reverse, wherein married women were more likely to experience unintended pregnancy [64,70]. This is perhaps due to the non-use or failure of contraceptives, which may be linked to partner refusal or beliefs about the safety or religious morality of using contraceptives. Regardless of marital status, the notion that unintended pregnancy may be linked to constraining beliefs reveals the importance of counselling and family planning, both in informal and healthcare settings. Thirdly, we found a contrary result that the odds of intended pregnancy decreased with motherhood experience. This is surprising, given that a logical association could be drawn that women with intended pregnancy are happier with motherhood than those with unintended pregnancy, a finding supported in a variety of contexts including Canada [25] and sub-Saharan Africa [71,72]. It could be theorized that mothers living with HIV who desired to bear children also suffered more emotional distress, as they were forced to contend with their strong desire for motherhood as well as the implications and potential risks of having a baby while living with HIV. WLHIV often worry about transmitting HIV to their baby, the safety of ART, and the effects of the pregnancy on their health [38]. Finally, being married and receiving support in infant feeding decisions increased the odds of intended pregnancy. This reflects the fact that the support of a partner is critical in reproductive as well as infant feeding decisions. Such support offers incentives to minimize risk of unintended pregnancy and vertical transmission of HIV.

4.3. Miami, Florida, United States

WLHIV in Miami who disclosed their HIV status had greater odds of intended pregnancy. This finding is consistent with other studies [32]. Disclosing one’s status to a partner may facilitate adherence to guidelines to mitigate vertical transmission of HIV, use of family planning methods to prevent an unwanted or untimed pregnancy, and access to social support. However, disclosure of HIV status may not always result in such straightforward outcomes for women. Therefore, care must be taken to provide WLHIV the needed support and counselling when they choose to disclose their HIV status, as it can lead to unexpected experiences of blame, abandonment, violence, stigma, or indifference [73,74]. We found contrariwise that receiving social support decreased the odds of intended pregnancy in Miami. This is unexpected, as other studies show the reverse association [75,76,77]. Finally, in Miami, the Influence of Specific Referents increased the odds of intended pregnancy. Specific referents including the healthcare provider of close family members who may be familiar with the guidelines for prevention of vertical transmission of HIV may provide tangible and informational support to WLHIV wishing to conceive.

5. Conclusions

The incidence of unintended pregnancy is more prevalent among Black women living with HIV in the North American cities (Ottawa, Canada and Miami, US) compared to Black non-immigrant women living with HIV the African city (Port Harcourt, Nigeria). Unique combinations of sociodemographic, sociocultural, and psychosocial factors influence pregnancy intention in each city, implying that policy to address reproductive health needs of WLHIV should be specific to the geographic context. However, a cross-cutting recommendation is that policy, programming, and practices that address the reproductive health needs of Black women should integrate educational, social, and economic empowerment resource components including Critical Health Literacy. These interventions should also include increasing access to sexual health services and counselling, strengthening social capital, and increasing employment for WLHIV. We also recommend the application of the health belief model in future studies, policies, programs, and practices that addresses unintended pregnancies among Black women living with HIV. This should go beyond promoting critical HIV literacy, to mitigating stigma and increasing uptake of antiretroviral treatment.

6. Study Limitations

Some authors argue that a dichotomous measure of pregnancy intention, such as intended versus unintended, can yield a mixed result, as unintended pregnancies combine wanted but mistimed pregnancies with unwanted pregnancies. We clarified to readers at the outset that we conceptualized unintended pregnancy as unwanted and mistimed pregnancies, and we had phrased the survey question to elicit data to reflect this combination. The study is cross-sectional and therefore limits our ability to infer a cause-and-effect relationship, but instead we established associations between variables. In addition, data collection was venue-based because of the hard-to-reach population of study, but we attempted to increase generalizability of our data by randomly selecting our sample of venues from a broad range of venues where WLHIV often meet.

Author Contributions

Conceptualization, E.B.E. and J.E.; methodology, E.B.E., J.C.P. and J.H.; software, E.B.E., J.C.P. and J.H.; validation, all authors; formal analysis, E.B.E. and J.C.P.; investigation, J.E., J.C.P., J.H., F.D. and A.E.; resources, J.E., J.C.P., J.H., F.D. and A.E.; data curation, E.B.E., J.H. and J.C.P.; writing E.B.E., R.E., A.W., M.F. and J.E.; review and editing, all authors; visualization, E.B.E.; supervision, J.E., J.C.P., J.H., F.D. and S.Y.; project administration, J.E. and J.H.; funding acquisition, J.E. All authors have read and agreed to the published version of the manuscript.

Funding

This paper is part of a broader Canadian Institutes of Health Research (CIHR Grant # 144831) funded study on Critical Research to Advance Infant Feeding (CRAIF).

Institutional Review Board Statement

Research Ethics Board approvals were obtained from (i) Health Sciences and Science Research Ethics Board at the University of Ottawa (certificate #H08–16-27), (ii) the Carleton University Research Ethics Board-A (CUREB-A, certificate #106300), (iii) the Social and Behavioral Institutional Review Board at Florida International University (certificate #105160), and (iv) the Research Ethics Committee at the University of Port Harcourt (certificate #UPH/CEREMAD/REC/04).

Informed Consent Statement

Participants provided written informed consent prior to engaging in the study. Before providing consent, they were informed of the potential risks associated with completing the questionnaire and that they would have limited direct benefit from their participation. They were informed that they could withdraw from the study at any time without any adverse effects. In addition to providing the written consent, participants were informed that completion of the questionnaire signified their informed consent to participate in the study.

Data Availability Statement

Data is unavailable due to ethical restrictions on the project.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Centers for Disease Control and Prevention. Unintended Pregnancy; Centers for Disease Control and Prevention: Atlanta, GA, USA, 2019.
  2. Santelli, J.S.; Rochat, R.; Hatfield-Timajchy, K.; Gilbert, B.C.; Curtis, K.M.; Cabral, R.; Hirsch, J.S.; Schieve, L.; Unintended Pregnancy Working Group. The Measurement and Meaning of Unintended Pregnancy. Perspect. Sex. Reprod. Health 2003, 35, 94–101. [Google Scholar] [CrossRef] [PubMed]
  3. World Health Organisation. High Rates of Unintended Pregnancies Linked to Gaps in Family Planning Services; WHO: Geneva, Switzerland, 2019. [Google Scholar]
  4. Bearak, J.; Popinchalk, A.; Ganatra, B.; Moller, A.-B.; Tunçalp, Ö.; Beavin, C.; Kwok, L.; Alkema, L. Unintended pregnancy and abortion by income, region, and the legal status of abortion: Estimates from a comprehensive model for 1990–2019. Lancet Glob. Health 2020, 8, e1152–e1161. [Google Scholar] [CrossRef] [PubMed]
  5. Finer, L.B.; Zolna, M.R. Declines in Unintended Pregnancy in the United States, 2008–2011. N. Engl. J. Med. 2016, 374, 843–852. [Google Scholar] [CrossRef] [PubMed]
  6. Salters, K.; Loutfy, M.; de Pokomandy, A.; Money, D.; Pick, N.; Wang, L.; Jabbari, S.; Carter, A.; Webster, K.; Conway, T.; et al. Pregnancy incidence and intention after HIV diagnosis among women living with HIV in Canada. PLoS ONE 2017, 12, e0180524. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  7. Oulman, E.; Kim, T.H.M.; Yunis, K.; Tamim, H. Prevalence and predictors of unintended pregnancy among women: An analysis of the Canadian Maternity Experiences Survey. BMC Pregnancy Childbirth 2015, 15, 260. [Google Scholar] [CrossRef] [Green Version]
  8. Schwartz, S.R.; Rees, H.; Mehta, S.; Venter, W.D.F.; Taha, T.E.; Black, V. High Incidence of Unplanned Pregnancy after Antiretroviral Therapy Initiation: Findings from a Prospective Cohort Study in South Africa. PLoS ONE 2012, 7, e36039. [Google Scholar] [CrossRef]
  9. Grilo, S.A.; Song, X.; Lutalo, T.; Mullinax, M.; Mathur, S.; Santelli, J. Facing HIV infection and unintended pregnancy: Rakai, Uganda, 2001–2013. BMC Women’s Health 2018, 18, 46. [Google Scholar] [CrossRef]
  10. Sutton, M.Y.; Zhou, W.; Frazier, E.L. Unplanned pregnancies and contraceptive use among HIV-positive women in care. PLoS ONE 2018, 13, e0197216. [Google Scholar] [CrossRef] [Green Version]
  11. Mosher, W.D.; Jones, J.; Abma, J.C. Intended and Unintended Births in the United States: 1982–2010; National Center for Health Statistics: Atlanta, GA, USA, 2012.
  12. Henshaw, S.K. Unintended pregnancy in the United States. Fam. Plan. Perspect. 1998, 30, 24–29+46. [Google Scholar] [CrossRef] [Green Version]
  13. Institute of Medicine (US) Committee on Unintended Pregnancy. The Best Intentions: Unintended Pregnancy and the Well-Being of Children and Families; National Academies Press: Washington, DC, USA, 1995. [Google Scholar]
  14. Daulaire, N. Promises to Keep: The Toll of Unintended Pregnancies on Women’s Lives in the Developing World, 1st ed.; Global Health Council: Washington, DC, USA, 2002; pp. 1–46. [Google Scholar]
  15. Bernstein, P.S.; Rosenfield, A. Abortion and maternal health. Int. J. Gynecol. Obstet. 1998, 63, S115–S122. [Google Scholar] [CrossRef]
  16. Kost, K.; Lindberg, L. Pregnancy intentions, maternal behaviors, and infant health: Investigating relationships with new measures and propensity score analysis. Demography 2015, 52, 83–111. [Google Scholar] [CrossRef] [Green Version]
  17. Forssman, H.; Thuwe, I. One hundred and twenty children born after application for therapeutic abortion refused. Their mental health, social adjustment and educational level up to the age of 21. Acta Psychiatr. Scand. 1966, 42, 71–88. [Google Scholar] [CrossRef]
  18. David, H.P.; Dytrych, Z.; Matjecek, Z.; Schüller, V. Born Unwanted: Developmental Effects of Denied Abortion; Springer Publishing Company: New York, NY, USA, 1988. [Google Scholar]
  19. Brittain, K.; Phillips, T.K.; Zerbe, A.; Abrams, E.J.; Myer, L. Long-term effects of unintended pregnancy on antiretroviral therapy outcomes among South African women living with HIV. Aids 2019, 33, 885–893. [Google Scholar] [CrossRef]
  20. Beyene, G.A.; Dadi, L.S.; Mogas, S.B. Determinants of HIV infection among children born to mothers on prevention of mother to child transmission program of HIV in Addis Ababa, Ethiopia: A case control study. BMC Infect. Dis. 2018, 18, 327. [Google Scholar] [CrossRef] [Green Version]
  21. Lewinsohn, R.; Crankshaw, T.; Tomlinson, M.; Gibbs, A.; Butler, L.; Smit, J. “This baby came up and then he said, “I give up!”: The interplay between unintended pregnancy, sexual partnership dynamics and social support and the impact on women’s well-being in KwaZulu-Natal, South Africa. Midwifery 2018, 62, 29–35. [Google Scholar] [CrossRef]
  22. Evans, A. The influence of significant others on Australian teenagers’ decisions about pregnancy resolution. Fam. Plan. Perspect. 2001, 33, 224–230. [Google Scholar] [CrossRef]
  23. Glander, S.S.; Moore, M.L.; Michielutte, R.; Parsons, L.H. The prevalence of domestic violence among women seeking abortion. Obs. Gynecol. 1998, 91, 1002–1006. [Google Scholar]
  24. Holmberg, L.I.; Wahlberg, V. The process of decision-making on abortion: A grounded theory study of young men in Sweden. J. Adolesc. Health 2000, 26, 230–234. [Google Scholar] [CrossRef]
  25. Loutfy, M.; Raboud, J.; Wong, J.; Yudin, M.; Diong, C.; Blitz, S.; Margolese, S.; Hart, T.; Ogilvie, G.; Masinde, K.; et al. High prevalence of unintended pregnancies in HIV-positive women of reproductive age in Ontario, Canada: A retrospective study. HIV Med. 2012, 13, 107–117. [Google Scholar] [CrossRef]
  26. Adeniyi, O.V.; Ajayi, A.I.; Moyaki, M.G.; Goon, D.T.; Avramovic, G.; Lambert, J. High rate of unplanned pregnancy in the context of integrated family planning and HIV care services in South Africa. BMC Health Serv. Res. 2018, 18, 140. [Google Scholar] [CrossRef]
  27. Iseyemi, A.; Zhao, Q.; McNicholas, C.; Peipert, J.F. Socioeconomic Status As a Risk Factor for Unintended Pregnancy in the Contraceptive CHOICE Project. Obstet. Gynecol. 2017, 130, 609–615. [Google Scholar] [CrossRef] [PubMed]
  28. Pallitto, C.C.; García-Moreno, C.; Jansen, H.A.F.M.; Heise, L.; Ellsberg, M.; Watts, C.; on behalf of the WHO Multi-Country Study on Women’s Health and Domestic Violence. Intimate partner violence, abortion, and unintended pregnancy: Results from the WHO Multi-country Study on Women’s Health and Domestic Violence. Int. J. Gynecol. Obstet. 2013, 120, 3–9. [Google Scholar] [CrossRef] [PubMed]
  29. Thindwa, D.; Landes, M.; Lettow, M.V.; Kanyemba, A.; Nkhoma, E.; Phiri, H.; Kalua, T.; Oosterhout, J.J.V.; Kim, E.J.; Barr, B.A.T.; et al. Pregnancy intention and contraceptive use among HIV-positive Malawian women at 4-26 weeks post-partum: A nested cross-sectional study. PLoS ONE 2019, 14, e0215947. [Google Scholar]
  30. Iliyasu, Z.; Abubakar, I.S.; Kabir, M.; Babashani, M.; Shuaib, F.; Aliyu, M.H. Correlates of fertility intentions among HIV/AIDS patients in northern Nigeria. Afr. J. Reprod. Health 2009, 13, 71–83. [Google Scholar]
  31. Berhan, Y.; Berhan, A. Meta-analyses of fertility desires of people living with HIV. BMC Public Health 2013, 13, 409. [Google Scholar] [CrossRef] [Green Version]
  32. Iyun, V.; Brittain, K.; Phillips, T.K.; Le Roux, S.; McIntyre, J.A.; Zerbe, A.; Petro, G.A.; Abrams, E.J.; Myer, L. Prevalence and determinants of unplanned pregnancy in HIV-positive and HIV-negative pregnant women in Cape Town, South Africa: A cross-sectional study. BMJ Open 2018, 8, e019979. [Google Scholar] [CrossRef]
  33. Oladapo, O.T.; Daniel, O.J.; Odusoga, O.L.; Ayoola-Sotubo, O. Fertility desires and intentions of HIV-positive patients at a suburban specialist center. J. Natl. Med. Assoc. 2005, 97, 1672–1681. [Google Scholar]
  34. Ogilvie, G.S.; Palepu, A.; Remple, V.P.; Maan, E.; Heath, K.; MacDonald, G.; Christilaw, J.; Berkowitz, J.; A Fisher, W.; Burdge, D.R. Fertility intentions of women of reproductive age living with HIV in British Columbia, Canada. Aids 2007, 21 (Suppl. 1), S83–S88. [Google Scholar] [CrossRef]
  35. Sowell, R.L.; Murdaugh, C.L.; Addy, C.L.; Moneyham, L.; Tavokoli, A. Factors influencing intent to get pregnant in HIV-infected women living in the southern USA. AIDS Care 2002, 14, 181–191. [Google Scholar] [CrossRef]
  36. Warren, C.E.; Abuya, T.; Askew, I. Family planning practices and pregnancy intentions among HIV-positive and HIV-negative postpartum women in Swaziland: A cross sectional survey. BMC Pregnancy Childbirth 2013, 13, 150. [Google Scholar] [CrossRef] [Green Version]
  37. Kirshenbaum, S.B.; Hirky, A.E.; Correale, J.; Goldstein, R.B.; Johnson, M.O.; Rotheram-Borus, M.J.; Ehrhardt, A.A. “Throwing the dice”: Pregnancy decision-making among HIV-positive women in four U.S. cities. Perspect. Sex. Reprod. Health 2004, 36, 106–113. [Google Scholar] [CrossRef]
  38. Sanders, L.B. Women’s voices: The lived experience of pregnancy and motherhood after diagnosis with HIV. J. Assoc. Nurses AIDS Care 2008, 19, 47–57. [Google Scholar] [CrossRef]
  39. Beyeza-Kashesya, J.; Wanyenze, R.K.; Goggin, K.; Finocchario-Kessler, S.; Woldetsadik, M.A.; Mindry, D.; Birungi, J.; Wagner, G.J. Stigma gets in my way: Factors affecting client-provider communication regarding childbearing among people living with HIV in Uganda. PLoS ONE 2018, 13, e0192902. [Google Scholar] [CrossRef] [Green Version]
  40. Gutin, S.A.; Harper, G.W.; Bitsang, C.; Moshashane, N.; Ramogola-Masire, D.; Harries, J.; Morroni, C. Perspectives about childbearing and pregnancy planning amongst people living with HIV in Gaborone, Botswana. Cult. Health Sex. 2020, 22, 1063–1079. [Google Scholar] [CrossRef]
  41. Nöstlinger, C.; Desjardins, F.; Dec, J.; Platteau, T.; Hasker, E. Child desire in women and men living with HIV attending HIV outpatient clinics: Evidence from a European multicentre study. Eur. J. Contracept. Reprod. Health Care 2013, 18, 251–263. [Google Scholar] [CrossRef]
  42. Sofolahan, Y.A.; Airhihenbuwa, C.O. Childbearing Decision Making: A Qualitative Study of Women Living with HIV/AIDS in Southwest Nigeria. AIDS Res. Treat. 2012, 2012, 478065. [Google Scholar] [CrossRef]
  43. Jones, D.L.; Cook, R.; Potter, J.E.; Miron-Shatz, T.; Chakhtoura, N.; Spence, A.; Byrne, M.M. Fertility Desires among Women Living with HIV. PLoS ONE 2016, 11, e0160190. [Google Scholar] [CrossRef] [Green Version]
  44. Phillips, J.C.; Etowa, J.; Hannan, J.; Etowa, E.B.; Babatunde, S. Infant feeding guideline awareness among mothers living with HIV in North America and Nigeria. Int. Breastfeed. J. 2020, 15, 27. [Google Scholar] [CrossRef] [Green Version]
  45. Hannan, J.; Etowa, J.B.; Babatunde, S.; Stephens, C.; Barfield, L.; Galarza, M.G.G.; Alharbi, M.M.; Reid, V.; Etowa, E.B.; Phillips, J.C. Determinants of Adherence to National Infant Feeding Guidelines by Black Mothers Living with HIV. Ethn. Dis. 2021, 31, 31–40. [Google Scholar] [CrossRef]
  46. Etowa, J.; Babatunde, S.; Hannan, J.; Etowa, E.B.; Mkandawire, P.; Loemba, H.; Phillips, J.C. Motherhood among Black women living with HIV: A “north-south” comparison of sociocultural and psychological factors. Health Care Women Int. 2021, 42, 304–322. [Google Scholar] [CrossRef]
  47. Etowa, J.; Hannan, J.; Etowa, E.B.; Babatunde, S.; Phillips, J.C. Determinants of infant feeding practices among Black mothers living with HIV: A multinomial logistic regression analysis. BMC Public Health 2021, 21, 663. [Google Scholar] [CrossRef] [PubMed]
  48. Matthey, S. Assessing the experience of motherhood: The Being a Mother Scale (BaM-13). J. Affect. Disord. 2011, 128, 142–152. [Google Scholar] [CrossRef] [PubMed]
  49. Broadhead, W.E.; Gehlbach, S.H.; de Gruy, F.V.; Kaplan, B.H. The Duke-UNC Functional Social Support Questionnaire. Measurement of social support in family medicine patients. Med. Care 1988, 26, 709–723. [Google Scholar] [CrossRef] [PubMed]
  50. Kaufman, K.J.; Hall, L.A. Influences of the social network on choice and duration of breast-feeding in mothers of preterm infants. Res. Nurs. Health 1989, 12, 149–159. [Google Scholar] [CrossRef] [PubMed]
  51. Cohen, S.; Kamarck, T.; Mermelstein, R. A global measure of perceived stress. J. Health Soc. Behav. 1983, 24, 385–396. [Google Scholar] [CrossRef]
  52. Williams, D.R. Measuring Discrimination. 2016. Available online: https://scholar.harvard.edu/files/davidrwilliams/files/measuring_discrimination_resource_june_2016.pdf (accessed on 10 January 2022).
  53. Etowa, J.; Nare, H.; Kakuru, D.M.; Etowa, E.B. Psychosocial Experiences of HIV-Positive Women of African Descent in the Cultural Context of Infant Feeding: A Three-Country Comparative Analyses. Int. J. Environ. Res. Public Health 2020, 17, 7150. [Google Scholar] [CrossRef]
  54. Michaels, E.; Thomas, M.; Reeves, A.; Price, M.; Hasson, R.; Chae, D.; Allen, A. Coding the Everyday Discrimination Scale: Implications for exposure assessment and associations with hypertension and depression among a cross section of mid-life African American women. J. Epidemiol. Community Health 2019, 73, 577–584. [Google Scholar] [CrossRef]
  55. Wilcher, R.; Cates, W. Reproductive choices for women with HIV. Bull. World Health Organ. 2009, 87, 833–839. [Google Scholar] [CrossRef]
  56. Ayalew, H.G.; Liyew, A.M.; Tessema, Z.T.; Worku, M.G.; Tesema, G.A.; Alamneh, T.S.; Teshale, A.B.; Yeshaw, Y.; Alem, A.Z. Prevalence and factors associated with unintended pregnancy among adolescent girls and young women in sub-Saharan Africa, a multilevel analysis. BMC Women’s Health 2022, 22, 464. [Google Scholar] [CrossRef]
  57. Beguy, D.; Mumah, J.; Gottschalk, L. Unintended pregnancies among young women living in urban slums: Evidence from a prospective study in Nairobi city, Kenya. PLoS ONE 2014, 9, e101034. [Google Scholar] [CrossRef] [Green Version]
  58. Wasswa, R.; Kabagenyi, A.; Atuhaire, L. Determinants of unintended pregnancies among currently married women in Uganda. J. Health Popul. Nutr. 2020, 39, 15. [Google Scholar] [CrossRef]
  59. Ikamari, L.; Izugbara, C.; Ochako, R. Prevalence and determinants of unintended pregnancy among women in Nairobi, Kenya. BMC Pregnancy Childbirth 2013, 13, 69. [Google Scholar] [CrossRef] [Green Version]
  60. Napyo, A.; Nankabirwa, V.; Mukunya, D.; Tumuhamye, J.; Ndeezi, G.; Arach, A.A.O.; Odongkara, B.; Waako, P.; Tylleskär, T.; Tumwine, J.K. Prevalence and predictors for unintended pregnancy among HIV-infected pregnant women in Lira, Northern Uganda: A cross-sectional study. Sci. Rep. 2020, 10, 16319. [Google Scholar] [CrossRef]
  61. Mayondi, G.K.; Wirth, K.; Morroni, C.; Moyo, S.; Ajibola, G.; Diseko, M.; Sakoi, M.; Magetse, J.D.; Moabi, K.; Leidner, J.; et al. Unintended pregnancy, contraceptive use, and childbearing desires among HIV-infected and HIV-uninfected women in Botswana: Across-sectional study. BMC Public Health 2016, 16, 44. [Google Scholar] [CrossRef] [Green Version]
  62. Teshale, A.B.; Tesema, G.A. Magnitude and associated factors of unintended pregnancy in Ethiopia: A multilevel analysis using 2016 EDHS data. BMC Pregnancy Childbirth 2020, 20, 329. [Google Scholar] [CrossRef]
  63. Wellings, K.; Jones, K.G.; Mercer, C.H.; Tanton, C.; Clifton, S.; Datta, J.; Copas, A.J.; Erens, B.; Gibson, L.J.; Macdowall, W.; et al. The prevalence of unplanned pregnancy and associated factors in Britain: Findings from the third National Survey of Sexual Attitudes and Lifestyles (Natsal-3). Lancet 2013, 382, 1807–1816. [Google Scholar] [CrossRef] [Green Version]
  64. Ameyaw, E.K.; Budu, E.; Sambah, F.; Baatiema, L.; Appiah, F.; Seidu, A.-A.; Ahinkorah, B.O. Prevalence and determinants of unintended pregnancy in sub-Saharan Africa: A multi-country analysis of demographic and health surveys. PLoS ONE 2019, 14, e0220970. [Google Scholar] [CrossRef] [Green Version]
  65. Craft, S.M.; Delaney, R.O.; Bautista, D.T.; Serovich, J.M. Pregnancy Decisions among Women with HIV. AIDS Behav. 2007, 11, 927–935. [Google Scholar] [CrossRef] [Green Version]
  66. Kennedy, V.L.; Serghides, L.; Raboud, J.M.; Su, D.; Blitz, S.; Hart, T.A.; Walmsley, S.L.; Angel, J.B.; Smaill, F.M.; Ralph, E.D.; et al. The importance of motherhood in HIV-positive women of reproductive age in Ontario, Canada. AIDS Care 2014, 26, 777–784. [Google Scholar] [CrossRef]
  67. Hubacher, D.; Mavranezouli, I.; McGinn, E. Unintended pregnancy in sub-Saharan Africa: Magnitude of the problem and potential role of contraceptive implants to alleviate it. Contraception 2008, 78, 73–78. [Google Scholar] [CrossRef]
  68. Calvert, C.; Baisley, K.; Doyle, A.M.; Maganja, K.; Changalucha, J.; Watson-Jones, D.; Hayes, R.J.; Ross, D.A. Risk factors for unplanned pregnancy among young women in Tanzania. BMJ Sex. Reprod. Health 2013, 39, e2. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  69. Jarolimova, J.; Kabakyenga, J.; Bennett, K.; Muyindike, W.; Kembabazi, A.; Martin, J.N.; Hunt, P.W.; Boum, Y.; Haberer, J.E.; Bangsberg, D.R.; et al. Contraceptive use following unintended pregnancy among Ugandan women living with HIV. PLoS ONE 2018, 13, e0206325. [Google Scholar] [CrossRef] [PubMed]
  70. Nyarko, S.H. Unintended Pregnancy among Pregnant Women in Ghana: Prevalence and Predictors. J. Pregnancy 2019, 2019, 2920491. [Google Scholar] [CrossRef] [PubMed]
  71. Brittain, K.; Mellins, C.A.; Remien, R.H.; Phillips, T.; Zerbe, A.; Abrams, E.J.; Myer, L. HIV-status disclosure and depression in the context of unintended pregnancy among South African women. Glob. Public Health 2019, 14, 1087–1097. [Google Scholar] [CrossRef]
  72. Peltzer, K.; Rodriguez, V.J.; Jones, D. Prevalence of prenatal depression and associated factors among HIV-positive women in primary care in Mpumalanga province, South Africa. SAHARA-J J. Soc. Asp. HIV/AIDS 2016, 13, 60–67. [Google Scholar] [CrossRef] [Green Version]
  73. Rahmawati, I.; Dewi, R. The experiences of HIV status disclosure among pregnant and postpartum women: A systematic review of qualitative evidence. In Proceedings of the 1st International Conference of Indonesian National Nurses Association ICINNA, Jakarta, Indonesia, 1–2 December 2018; Volume 1, pp. 31–41. [Google Scholar]
  74. Mkandawire, A.K.; Jumbe, V.; Nyondo-Mipando, A.L. To disclose or not: Experiences of HIV infected pregnant women in disclosing their HIV status to their male sexual partners in Blantyre, Malawi. BMC Public Health 2022, 22, 1552. [Google Scholar] [CrossRef]
  75. Kendall, C.; Afable-Munsuz, A.; Speizer, I.; Avery, A.; Schmidt, N.; Santelli, J. Understanding pregnancy in a population of inner-city women in New Orleans--results of qualitative research. Soc. Sci. Med. 2005, 60, 297–311. [Google Scholar] [CrossRef]
  76. Samandari, G.; Speizer, I.; O’Connell, K. The Role of Social Support and Parity On Contraceptive Use in Cambodia. Int. Perspect. Sex. Reprod. Health 2010, 36, 122–131. [Google Scholar] [CrossRef]
  77. Moseson, H.; Dehlendorf, C.; Gerdts, C.; Vittinghoff, E.; Hiatt, R.A.; Barber, J. No one to turn to: Low social support and the incidence of undesired pregnancy in the United States. Contraception 2018, 98, 275–280. [Google Scholar] [CrossRef]
Women 03 00023 g001 550
Figure 1. Percent of mothers who had intended versus unintended pregnancy.
Figure 1. Percent of mothers who had intended versus unintended pregnancy.
Women 03 00023 g001
Table
Table 1. Descriptive statistics of sociodemographic, sociocultural, and psychosocial variables.
Table 1. Descriptive statistics of sociodemographic, sociocultural, and psychosocial variables.
Descriptive VariablesOttawa, Canada
(N = 89)		Port Harcourt, Nigeria
(N = 400)		Miami, Florida, United States
(N = 201)
Sociodemographic variables:
Age (years), (m ± SD)36.63 ± 6.4134.67 ± 5.6532.40 ± 5.93
Marital status (married), n (%)29 (33.33)340 (85.21)121 (60.80)
Household size (headcount), m (range)3.70 (6)4.48 (10)3.68 (8)
Children born after HIV diagnosis (average age), (m ± SD)8.15 ± 5.554.12 ± 3.415.31 ± 3.29
Years of formal education, (m ± SD)14.34 ± 2.0212.36 ± 2.6714.52 ± 1.27
Employment status (employed), n (%)46 (52.90)273 (68.40)42 (23.10)
Psychosocial variables:
Disclosure of HIV status, ranked score m (Range)1.30(2)1.67 (2)1.39 (2)
Motherhood (scale score), benchmark = 52,
α = (m ± SD)		42.99 ± 7.0228.58 ± 6.7336.66 ± 10.69
Social support (scale score), benchmark = 35,
α = (m ± SD)		24.77 ± 6.5520.72 ± 6.1821.90 ± 8.10
Gets support in infant feeding decisions, n (%)49 (56.3)330 (83.3)89 (48.90)
Influence of specific referents (ranked score), m (Range)18.53 (45)21.72 (45)12.70 (45)
HIV knowledge (ranked score), m (Range)2.40 (3)2.65 (3)2.40 (3)
Hypervigilance (scale score); benchmark = 20,
α = 0.71; (m ± SD)		12.70 ± 4.9810.21 ± 5.187.57 ± 5.28
Perceived stress (scale score); benchmark = 40,
α = 0.76; (m ± SD)		16.20 ± 6.5122.10 ± 4.1721.09 ± 6.91
Discrimination (scale score); benchmark = 50,
α = 0.96; (m ± SD)		24.84 ± 15.957.28 ± 9.4515.55 ± 14.36
Table
Table 2. Correlates of intended pregnancies among Black mothers living with HIV: Hierarchical Binary Logistic Regression Analysis.
Table 2. Correlates of intended pregnancies among Black mothers living with HIV: Hierarchical Binary Logistic Regression Analysis.
Dependent Variable: Intended (1) versus Unintended (0) PregnancyOttawa, CanadaPort Harcourt, NigeriaMiami, FL, US
Independent variablesOR (95% CI)OR (95% CI)OR (95% CI)
Block 1 (sociodemographic variables):
Age (years)-0.93 *** (0.88/0.98)0.94 (0.88/1.00)
Marital status (married = 1, otherwise = 0)1.20 (0.28/5.34)2.90 *** (1.43/5.88)0.8 (0.38/1.70)
Household size (number of persons)0.56 ** (0.36/0.87)--
Mean age of children born since HIV diagnosis--1.08 (0.95/1.23)
Years of formal education0.83 (0.57/1.23)0.97 (0.87/1.01)1.27 (0.94/1.70)
Employed (yes = 1, No = 0)7.84 ** (1.52/40.54)0.8 (0.43/1.51)-
Block 2 (Socio-cultural and psychosocial variables):
Disclosure of HIV status (ranked score)-1.38 (0.77/2.45)1.73 * (1.01/2.97)
Motherhood experience (scale score)0.98 (0.85/1.11)0.96 * (0.92/0.99)-
Social support (scale score)1.02 (0.91/1.135)0.97 (0.92/1.02)0.95 * (0.91/1.00)
Gets support in infant feeding decisions (Yes = 1, No = 0)-3.77 *** (1.98/7.19)-
Influence of specific referents (ranked score)1.04 (0.42/2.60)-1.68 ** (1.13/2.52)
HIV knowledge (ranked score)3.13 *** (1.42/6.90)1.12 (0.72/1.73)-
Hypervigilance (scale score)-0.97 (0.91/1.04)1.01 (0.95/1.10)
Perceived stress (scale score)0.92 (0.8/1.06)-1.01 (0.96/1.06)
HIV Discrimination (scale score)1.07 * (1.01/1.13)-1.01 (0.98/1.04)
Model summary:
Chi-square statistics (X2)28.47 ***41.38 ***20.54 *
Error estimate (-2LL)61.88321.08189.55
Reduction of -2LL after inclusion of Block 213.9427.4714.68
Observations used in analysis (%)75.396.585.07
Model accuracy (%)77.682.472.5
*** p < 0.001, ** p < 0.01, and * p < 0.05.
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Etowa, E.B.; Edet, R.; Willett, A.; Fseifes, M.; Diorgu, F.; Hannan, J.; Phillips, J.C.; Yaya, S.; Etokidem, A.; Etowa, J. Understanding Pregnancy Intentions among Black Women Living with HIV in Two North American Cities and One African City. Women 2023, 3, 310-321. https://doi.org/10.3390/women3020023

AMA Style

Etowa EB, Edet R, Willett A, Fseifes M, Diorgu F, Hannan J, Phillips JC, Yaya S, Etokidem A, Etowa J. Understanding Pregnancy Intentions among Black Women Living with HIV in Two North American Cities and One African City. Women. 2023; 3(2):310-321. https://doi.org/10.3390/women3020023

Chicago/Turabian Style

Etowa, Egbe B., Ruby Edet, Andrea Willett, Manal Fseifes, Faith Diorgu, Jean Hannan, J. Craig Phillips, Sanni Yaya, Aniekan Etokidem, and Josephine Etowa. 2023. "Understanding Pregnancy Intentions among Black Women Living with HIV in Two North American Cities and One African City" Women 3, no. 2: 310-321. https://doi.org/10.3390/women3020023

APA Style

Etowa, E. B., Edet, R., Willett, A., Fseifes, M., Diorgu, F., Hannan, J., Phillips, J. C., Yaya, S., Etokidem, A., & Etowa, J. (2023). Understanding Pregnancy Intentions among Black Women Living with HIV in Two North American Cities and One African City. Women, 3(2), 310-321. https://doi.org/10.3390/women3020023

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