Sage Journals: Discover world-class research

Abstract

Background:

Zambia is one of the countries in sub-Saharan Africa with a high prevalence of human immunodeficiency virus among women of reproductive age. Notably, the literature shows that human immunodeficiency virus status is one of the factors that influence fertility intention among women of reproductive age. With increased access, uptake and coverage of anti retroviral therapy, there is a need to understand the influence of human immunodeficiency virus status on fertility intentions of women of reproductive age in Zambia.

Objectives:

The purpose of this study was to determine the fertility intentions of both mothers living with human immunodeficiency virus and mothers living without human immunodeficiency virus in Zambia.

Design:

This study adopted a cross-sectional design using data collected by the Zambia Demographic and Health Survey conducted in 2018. The study sample comprised 7983 mothers in the reproductive age (15–49 years), of which 6704 were mothers living without human immunodeficiency virus and 1279 were mothers living with human immunodeficiency virus.

Methods:

Here, we determined the fertility intentions of mothers living with human immunodeficiency virus and mothers living without human immunodeficiency virus using secondary data. Multivariable logistic regression models were used to determine the association of individual and household socio-demographic factors on fertility intentions of mothers living with human immunodeficiency virus and mothers living without human immunodeficiency virus in Zambia.

Results:

Fertility intention among mothers living with human immunodeficiency virus was 42.1% while that on mothers living without human immunodeficiency virus was 55.5%. Regardless of human immunodeficiency virus status, fertility intention reduced with increasing age. Mothers aged 35–49 years who were living with human immunodeficiency virus (adjusted odds ratio = 0.12, 95% confidence interval = 0.06–0.24) and mothers aged 35–49 years who were living without human immunodeficiency virus (adjusted odds ratio = 0.18, 95% confidence interval = 0.13–0.26) had lower odds of intention to have another child compared to mothers aged 15–24 years. Furthermore, married mothers living with human immunodeficiency virus and those living without human immunodeficiency virus had increased odds of intention of having another child (adjusted odds ratio = 2.52, 95% confidence interval = 1.36–4.66) and (adjusted odds ratio = 3.21, 95% confidence interval = 2.36–4.36), respectively.

Conclusion:

The study has established that age, marital status, parity and employment status were associated with fertility intention among women living with and without human immunodeficiency virus. The results necessitate the need for enhanced maternal health education for mothers regardless of human immunodeficiency virus status. Furthermore, there is a need for continuous counselling for both women living with human immunodeficiency virus and without human immunodeficiency virus during their routine human immunodeficiency virus care, to improve and enhance pregnancy outcomes.

Keywords

fertility intention human immunodeficiency virus reproductive health women Zambia

Introduction

Human immunodeficiency virus (HIV) continues to be a serious public health problem globally affecting the quality of life among the patients. By the end of 2020, approximately 37.7 million people were estimated to be living with HIV around the world^1
–3 while recent studies show that about 24.5 million people were receiving anti-retroviral therapy (ART) as of the end of 2020.^4,5 In Sub-Saharan Africa (SSA), the burden is more pronounced in women of childbearing age, with four out of every five new infections being reported among women in this group.⁶ In Zambia, the prevalence of HIV as of 2018 was 14.2% among women while it was 7.5% among men.⁷

Advances in HIV research, improved access to ART and care, have transformed HIV into a chronic condition, increasing the survival time of patients.^8
–11 Furthermore, this has increased the desire of the patients to consider parenthood. According to Kodzi et al.,¹² parenthood intentions play an important role in influencing fertility activities of women. Therefore, information relating to fertility intentions is vital for provide insights into the future direction of fertility patterns.^7,13,14 Furthermore, understanding the fertility intentions of people living with HIV is critical in planning and delivering a responsive reproductive health system as part of a continuum of HIV care in developing countries.^15,16

Fertility intention refers to an individual or couple’s desire, plans and decisions regarding having another child.¹⁷ The 2018 Zambia Demographic and Health Survey (ZDHS) show that 62% of married mothers had intention to have another child.¹⁸ Emerging evidence indicates that HIV status influences fertility intentions of women of reproductive age (15–49 years).^19
–21 For instance, a study from Kenya found that fertility intentions among women living with HIV (WLWH) was 30%²⁰ while a study from Ethiopia revealed that 42% of WLWH wanted to have another child.¹ On the contrary, Zambia recorded a reduction in the proportion of women of reproductive age who wanted more children from 76% to 62% between 1992 and 2018.^7,22 However, it remains the highest in the SSA region.^23
–26 Although ART has had a positive influence on the quality of life among WLWH in Zambia,^27,28 reproductive assistance among these women remains critical to improve child bearing decisions. In resource-constrained settings, identifying factors that influence fertility intentions among WLWH is important for developing strategies and steering appropriate prevention policies that enhance service delivery and reproductive health among this population. Here, we used nationally representative data coming from the 2018 ZDHS to identify factors that influence fertility intention among both WLWH and mothers living without HIV in Zambia.

Methods and data

Data source

The study was based on secondary analysis of the existing national level data from the 2018 ZDHS programme.¹⁸ The ZDHS is a nationally representative household survey conducted by the Zambia Statistics Agency with support from global partners, including the ICF International and United States Agency for International Development (USAID). A detailed description of the methods used in the surveys is included in reports of Demographic and Health Surveys (DHS) conducted in Zambia.¹⁸ The DHS uses a two-stage cluster sampling design to select enumeration areas (EAs) in the first stage and households in the second stage. The nature of DHS data allows for comparisons between variables over time, thus allowing monitoring of changes in the indicators of variables of interest in different geographical areas. Women aged 15–49 years of selected households who had accepted to participate in the study were also enrolled in the survey. The data analysed in this article relate to women aged 15–49 years. The 2018 DHS captured 13,683 women of reproductive age. For this study, we extracted all relevant variables from the individual woman recode file (IR file) in the 2018 DHS data. The individual recode file was then merged with the HIV data file (AR). All women’s data with successful merged HIV status were retained in the data set. Furthermore, all women who reported ever having at least one child ever born and those who had complete information about desire for more children were included in the analysis. The selection criteria for the analytical sample size are described in Figure 1.

Figure 1.

Description of sample derivation criteria.

Outcome variable

The outcome variable of interest in this study was fertility intention, which was measured using a question ‘Would you like to have another child, or would you prefer not to have any more children?’ asked to all women in the DHS who had at least reported to have a parity of one. These women were asked if they had intentions of having another child or not. The study included only women who reported having at least one biological child. This is because the concept of fertility intention refers to a decision by a couple or a woman to have another child. Therefore, the intention to have another child was measured only among women who had at least one child. Outcome variable was binary and was coded as ‘1’ for women who had intentions of having another child and ‘0’ for those who had no fertility intentions.

Independent factors

Based on the literature reviewed, we classified the factors that could potentially influence fertility intentions as socio-economic, demographic and individual-level factors.^19,29
–31 The DHS reference materials and data collection forms were used to identify the individual-level independent factors. The predictor variables included age of woman, which was categorized as (15–24, 25–34 and 35–49 years); current marital status was categorized as (never married, currently married/living with partner and formally married); residence was categorized as (urban, rural); education was classified as (no education, primary, secondary, tertiary); household wealth index was categorized as (poor, middle, rich); parity was classified as (1–3 children, 4–6 children, 7 children and more); contraceptive use was categorized as (not using, using); employment status was categorized as (employed, unemployed) and experience of pregnancy loss was coded as (no, yes).

Statistical analysis

Analysis of data was performed using Stata version 14.2 (StataCorp Inc., College Station, TX, USA) taking into consideration survey design, cluster effect and post-stratification weights. Key socio-economic and demographic factors were described and expressed in frequency and percentage distributions. Exploratory bivariate analysis was carried out to determine the association between the fertility intentions of women and the selected independent variables. A multivariate binary logistic regression model was applied on the data to determine the associations of several individual-level factors on fertility intention in Zambia. Odds ratios with corresponding 95% confidence intervals (CIs) were reported. All independent factors from the bivariate analyses which had p-value of less than 0.000 were included in multivariate analysis, regardless of their level of significance. In multivariable logistic regression analysis, variable with p < 0.05 were considered to be significantly associated fertility intention. This study followed the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) guidelines, to ensure comprehensive reporting and adherence to methodological standards in the design, analysis and interpretation of the survey data.

Results

Description of characteristics of sampled women

Table 1 shows the distribution of respondents based on the selected background characteristics. Results show that most (51.5%) of the WLWH were in the age group 35–49 years. Among the mothers living without HIV respondents, most (37.4%) were in the age range 25–34 years. In terms of residence, most of the WLWH (64.9%) lived in urban areas. Most (61.9%) of the mothers living without HIV were living in rural areas. The distribution by education level shows most of the study participants had attained primary regardless of the HIV status. Similarly, results show that regardless of the HIV status, most of the participants had 1–3 children ever born. Furthermore, results show that most of the study participants were unemployed regardless of the HIV status.

Table 1.

Percent distribution of background characteristics of mothers living with HIV and mothers living without HIV (15–49 years), 2018 DHS, Zambia (N = 7983).

Background characteristics	Mothers living with HIV (n = 1279)	Mothers living without HIV (n = 6704)	p
Background characteristics	(n, %)	(n, %)	p
Age (years)			<0.001***
15–24	145 (10.6%)	1839 (27.7%)
25–34	524 (37.9%)	2495 (37.6%)
35–49	712 (51.5%)	2310 (34.7%)
Residence			<0.001***
Urban	896 (64.9%)	2534 (38.1%)
Rural	485 (35.1%)	4110 (61.9%)
Education			<0.001***
No education	86 (6.3%)	656 (9.9%)
Primary	623 (45.1%)	3398 (51.2%)
Secondary	590 (42.7%)	2265 (34.1%)
Tertiary	81 (5.9%)	323 (4.9%)
Wealth index			<0.001***
Poor	298 (21.6%)	2887 (43.5%)
Middle	233 (16.9%)	1243 (18.7%)
Rich	850 (61.5%)	2513 (37.8%)
Marital status			<0.001***
Never married	88 (6.4%)	503 (7.6%)
Currently married	885 (64.0%)	5376 (80.9%)
Formerly married	408 (29.6%)	764 (11.5%)
Parity			<0.001***
1–3	718 (51.9%)	3510 (52.8%)
4–6	546 (39.6%)	2054 (30.9%)
7+	116 (8.5%)	1079 (16.3%)
Employment status			0.1555
Employed	914 (33.8%)	3973 (40.1%)
Unemployed	467 (66.2%)	2658 (59.9%)

HIV: human immunodeficiency virus; DHS: demographic and health survey.

***

p < 0.001

Distribution of fertility intentions of mothers living with HIV and mothers living without HIV

Table 2 shows the distribution of fertility intention of WLWH and mothers living without HIV by background characteristics. Overall, the results show that about 42.1% (n = 582) of the WLWH had intention of having more children while about 55% (n = 3687) of mothers living without HIV had intention of having more children. We further observed that among both WLWH and mothers living without HIV, older women (aged 35–49 years) had lower rates of fertility intention to have more children compared to young mothers (15–24 years). In terms of residence, 44.1% (n = 395) of WLWH who wanted more children were from urban areas while among those who were mothers living without HIV, rural areas had more women who wanted more children, 57.4% (n = 2354). Regardless of the HIV status, it is observed that women with secondary and tertiary education comprised the highest proportions of women wanting more children in the future. The results also showed that 45% (n = 380) of the women who were WLWH and had intentions of having more children belonged to rich households. On the contrary, 58.5% (n = 1690) of mothers living without HIV who belonged to poor households had intention to have more children (Table 2).

Table 2.

Percent distribution of mother’s (15–49 years) fertility intentions by selected demographic and socio-economic characteristics according to HIV status, ZDHS 2018 (N = 7983).

Background characteristics	Mothers living with HIV (N = 1382)	p	Mothers living without HIV (N = 6645)	p
Background characteristics	Want another child (n, %)	p	Want another child (n, %)	p
Age (years)		<0.001***		<0.001***
15–24	121 (83.1%)		1565 (85.1%)
25–34	306 (58.3%)		1657 (66.4%)
35–49	156 (21.9%)		465 (20.1%)
Residence		0.173		<0.05**
Urban	396 (44.1%)		1330 (52.5%)
Rural	187 (38.4%)		2357 (57.4%)
Education		<0.001***		<0.001***
No education	27 (31.2%)		272 (41.6%)
Primary	218 (35.0)		1756 (51.7%)
Secondary	297 (50.4%)		1464 (64.6%)
Tertiary	40 (48.5%)		194 (60.0%)
Wealth index		<0.05**		0.181
Poor	114 (38.4%)		1690 (58.5%)
Middle	88 (37.7%)		658 (52.9%)
Rich	380 (44.7%)		1336 (53.3%)
Marital status		<0.001***		<0.001***
Never married	49 (55.8%)		327 (65.1%)
Currently married	456 (51.6%)		3164 (58.9%)
Formerly married	77 (18.8%)		195 (25.6%)
Parity		<0.001***		<0.001***
1–3	449 (62.6%)		2750 (78.4%)
4–6	129 (23.7%)		806 (39.3%)
7+	3 (2.9%)		131 (12.1%)
Contraceptive use		<0.001***		0.777
Using	235 (42.7%)		1886 (58.5%)
Not using	347 (41.8%)		1801 (52.6%)
Employment status		<0.001***		<0.05**
Employed	362 (39.6%)		2015 (50.7%)
Unemployed	220 (47.1%)		1659 (62.4%)
Experienced pregnancy loss		0.307		0.109
No	503 (41.2%)		3293 (55.7%)
Yes	78 (49.1%)		394 (53.5%)
Total number of women desiring another child	582 (42.1%)	<0.001***	3687 (55.5%)	<0.001***

HIV: human immunodeficiency virus; ZDHS: Zambia Demographic and Health Survey.

p < 0.01; ***p < 0.001.

Determinants of fertility intention of mothers living with HIV and mothers living without HIV

When we controlled for the covariate in the final multivariate models, we observed that among WLWH, age of a woman, marital status and parity were the predictors of fertility intentions among WLWH. Among mothers living without HIV, age, place of residence, wealth status, marital status and experience of pregnancy loss were associated with their fertility intentions. WLWH aged 25–34 years (adjusted odds ratio (aOR) = 0.37, 95% CI = 0.19–0.71) and those aged 35–49 years (aOR = 0.12, 95% CI = 0.06–0.24) had lower odds of desire for more children compared to women aged 15–19 years. WLWH who were married (aOR = 2.52, 95% CI = 1.36–4.66) were more likely to have intention to have more children compared to the unmarried. WLWH who had 4–6 children (aOR = 0.24, 95% CI = 0.15–0.37) or 7+ children (aOR = 0.07, 95% CI = 0.01–0.07) had lower odds of fertility intentions compared to those with 1–3 children.

Results further show that mothers living without HIV aged 25–34 years (aOR = 0.68, 95% CI = 0.52–0.88) and those aged 35–49 years (aOR = 0.13, 95% CI = 0.13–0.26) had lower odds of fertility intention compared to their counterparts aged 15–19 years. In addition, mothers living without HIV from moderate wealth status households (aOR = 0.75, 95% CI = 0.61–0.91) or rich households (aOR = 0.58, 95% CI = 0.38–0.87) and with 4–6 children (aOR = 0.22, 95% CI = 0.18–0.27) or 7+ children (aOR = 0.06, 95% CI = 0.04–0.08) were less likely to have a desire for more children. Those living in rural areas (aOR = 1.46, 95% CI = 1.14–1.86), married (aOR = 3.21, 95% CI = 2.36–4.36) and those who experienced pregnancy loss (aOR = 1.35, 95% CI = 1.07–1.69) were more likely to have fertility intentions compared to their defined comparison group (Table 3).

Table 3.

Multivariable logistic regression analysis of the associations between mother’s characteristics and fertility intentions by HIV status, ZDHS 2018 (N = 7983).

Background characteristics	Mothers living with HIV		Mothers living without HIV
Background characteristics	Adjusted odds ratio (AOR)	95% confidence interval	Adjusted odds ratio (AOR)	95% confidence interval
Age (years)
15–24	1		1
25–34	0.37**	0.19–0.71	0.68**	0.52–0.88
35–49	0.12***	0.06–0.24	0.18***	0.13–0.26
Residence
Urban	1		1
Rural	0.96	0.59–1.56	1.46**	1.14–1.86
Education level
No education	1		1
Primary	0.95	0.46–1.98	1.11	0.86–1.41
Secondary	1	0.47–2.14	1.26	0.96–1.65
Tertiary	0.96	0.36–2.53	1.34	0.86–2.09
Wealth quantile
Poor	1		1
Middle	0.76	0.43–1.35	0.75**	0.61–0.91
Rich	0.62	0.36–1.09	0.58***	0.45–0.74
Marital status
Never married	1		1
Currently married	2.52**	1.36–4.66	3.21***	2.36–4.36
Formerly married	0.50*	0.27–0.95	0.58**	0.38–0.87
Parity
1–3	1		1
4–6	0.24***	0.15–0.37	0.22***	0.18–0.27
7+	0.03***	0.01–0.07	0.06***	0.04–0.08
Employment status
Unemployed	1		1
Employed	1.07	0.74–1.55	0.98	0.79–1.23
Contraception use
Not using	1		1
Using	0.9	0.64–1.28	0.99	0.82–1.19
Experienced pregnancy loss
No	1		1
Yes	1.33	0.84–2.10	1.35*	1.07–1.69

HIV: human immunodeficiency virus; ZDHS: Zambia Demographic and Health Survey.

p < 0.05; **p < 0.01; ***p < 0.001.

Table 4 presents results from the multivariable logistic regression model which included HIV status of a mother as a covariate. We observed that age of a mother, place of residence, marital status, wealth quintile, pregnancy loss and parity were the predictors of fertility intention. Mothers aged 25–34 years (aOR = 0.59; 95% CI = 0.48–0.72) and those aged 35–49 years (aOR = 0.72; 95% CI = 0.13–0.21) were less likely to prefer another child compared with mothers aged 15–24 years. Women living in rural areas (aOR = 1.36, 95% CI = 1.11–1.68) or those in marital union (aOR = 3.02, 95% CI = 2.34–3.89) had higher odds of intending to have another child compared to their counterparts. Furthermore, mothers who belonged to households whose wealth status is classified as moderate (aOR = 0.77, 95% CI = 0.65–0.93) or rich (aOR = 0.63, 95% CI = 0.48–0.75) had lower odds of intending to have another child compared with mothers from households classified as poor. Regarding parity, mothers who had 4–6 children ever born (aOR = 0.24, 95% CI = 0.19–0.28) or 7+ children (aOR = 0.07, 95% CI = 0.05–0.09) had lower odds intending to have another child compared to those with 1–3 children. Mothers who experienced a pregnancy loss (aOR = 1.35, 95% CI = 1.10–1.63) had higher odds of intending to have another child (Table 4).

Table 4.

Multivariable logistic regression analysis of the associations of predictors on fertility intention, ZDHS 2018 (N = 7983).

Background characteristics	Want another child
Background characteristics	Adjusted odds ratio (AOR)	95% confidence interval
Age (years)
15–24	1
25–34	0.59***	0.48–0.72
35–49	0.72***	0.13–0.21
HIV status
Living without HIV	1
Living with HIV	0.91	0.68–1.21
Residence
Urban	1
Rural	1.36**	1.11–1.68
Education level
No education	1
Primary	1.08	0.86–1.36
Secondary	1.21	0.94–1.56
Tertiary	1.26	0.86–1.83
Wealth quantile
Poor	1
Middle	0.77**	0.65–0.93
Rich	0.61***	0.48–0.75
Marital status
Never married	1
Currently married	3.02***	2.34–3.89
Formerly married	0.59***	0.44–0.79
Parity
1–3	1
4–6	0.24***	0.19–0.28
7+	0.067***	0.05–0.09
Employment status
Unemployed	1
Employed	1.01	0.87–1.21
Contraception use
Not using	1
Using	1.01	0.86–1.19
Experienced pregnancy loss
No	1
Yes	1.35**	1.10–1.63

ZDHS: Zambia Demographic and Health Survey; HIV: human immunodeficiency virus.

p < 0.01; *** p < 0.001.

Discussion

This study sought to analyse the influence of HIV status on fertility intention of women in Zambia. The study applied multivariable binary logistic regression models on 2018 ZDHS data to better understand the predictors of fertility intentions among women. Overall, the results show age of the mother, place of residence, household wealth status, marital status, parity and experience of a pregnancy loss were associated with fertility intention in Zambia. Forty-two percent of WLWH had an intention to have another child. On the contrary, about 56% of the women living without HIV had an intention to have another child, although there was no significant difference between the groups after controlling for other factors. The distribution by residence shows that 38.4% of WLWH from rural areas compared to 57.4% of WLWH in rural areas. Similarly, results showed that married WLWH (51.6%) compared to (58.9%) of the married mothers living without HIV had intention for another child. However, in terms of comparison by age, the results showed that 21.9% of WLWH in the age group 35–49 years had of intention to have another child compared to 20.1% of the mothers living without HIV.

The results further show that, among both WLWH and mothers living without HIV, fertility intentions reduced with age and parity. In addition, women from wealthy families had reduced odds of fertility intentions regardless of their HIV status. These results have implications for designing of appropriate sexual and reproductive health programmes to enhance access to family planning services, especially among WLWH.

Previously, several studies^31
–34 examined fertility intention among WLWH of reproductive age. To better understand individual-level factors among women, we disaggregated our analyses by a woman’s HIV status, given the diverse health service needs and access. Our study established that variations in the factors influencing fertility intention. Fertility intentions among WLWH were influenced by age, marital status and parity, while among those who were mothers living without HIV, fertility intentions were influenced by age, residence, wealth index, marital status and experience of pregnancy loss. However, results in the final analysis model show that HIV status of mothers did not influence fertility intention in Zambia. Mothers living with HIV had the same fertility intention as that of mothers who were living with no HIV.

We observed that in both WLWH and mothers living without HIV, fertility intentions waned with an increase in age, suggesting the importance of age in determining a woman’s reproductive intentions.^30,35
–38 Although no reasons were explored for this, we postulate that maternal health clinics attended by expecting mothers engage in health education related to obstetric and age. Furthermore, studies conducted in SSA suggest that pregnancy in older women such as those aged 35 years and above may have increased risks of negative pregnancy outcomes and obstetric complications such as intrauterine foetal death, pregnancy-induced hypertension and gestational diabetes. This may thus account for the reduction in the fertility intentions with age, as women may be discouraged to engage in childbearing with advance in age.^39
–41 We also postulate that changes in the economic conditions and demands may discourage women from having more children and as they would have reached their intended family sizes thus engage themselves in using contraceptives to reduce the risks of unplanned pregnancies. Our results are consistent with those of other related studies conducted in Malawi, Ethiopia and South Africa that found that fertility intentions among women reduced with age.^1,13,21,31 Furthermore, our findings also agree with earlier studies which observed that fertility intention reduced by 12.9% among women who had 2–3 children.^31,42

Our study findings have also shown that mothers living without HIV in marital union had higher likelihood of fertility intentions compared to mothers who were never married. In the Zambian context, this is due to women trying to respond to family or societal pressure to reach their desire family size. Thus, there is an urgent need to consider implementing community led family planning education programmes championing reproductive behaviour change among women, especially those coming from rural settings where access to reproductive health information could be limited. Furthermore, higher odds of fertility intentions among women from rural areas may be because of limited health education about family planning, unmet needs of family planning or both^43
–47 while traditional demands and cultural beliefs of having larger family may also be the reasons for higher odds of fertility intentions among mothers living without HIV in rural areas. Our findings are in agreement with findings of Ahinkorah et al.⁴⁸ and Ewemooje et al.,⁴⁹ which also found that women living in rural areas were more likely to have a desire for more children than their counterparts living in urban areas. This could be because of strong cultural and social norms that emphasize the importance of large families and view childbearing as a central aspect of wealth in rural settings.

Consistent with SDG (Sustainable Development Goal) 3, which seeks to ensure healthy lives and promote well-being of women,^50,51 our findings show the need to enhance reproductive health education among women of reproductive age in Zambia, especially women of childbearing age. Although fertility intentions of WLWH in Zambia appeared lower in univariate analysis than when compared to their counterparts who are mothers living without HIV, this finding did not remain significant after adjusting for other factors. Regardless, the proportion of WLWH who still have a desire for more children is considerably high. Strengthening maternal health education targeted at adolescents and young WLWH is key to further reduce the risk of mother-to-child transmission of HIV in the country.⁵² Therefore, understanding issues relating to knowledge of WLWH regarding prevention of mother-to-child transmission of HIV and their access to reproductive health services is key in informing strengthening family planning policy to address of high fertility intention among WLWH with varied reproductive health needs.

Given that the ZDHS data were collected through cross-sectional design, the analysis done on the data can only permit measurement associations between some independent variables and the outcome variable of interest. As a result, it is important to note that only associations were investigated in this study, and no attempt was made to determine whether there was a causal relationship. There could be a variety of other factors that influence fertility intentions among WLWH and mothers living without HIV such as cultural beliefs or social norms. For example, the reasons why WLWH still wanted to have children despite living with HIV could not be answered due to lack of qualitative variables in ZDHS data set. Furthermore, the ZDHS did not apply power analysis to select samples of WLWH and women living without HIV. Thus, the sample sizes may not be sufficient to detect real differences in fertility preference. Nevertheless, the DHS being a nationally representative is robust to produce findings that can be generalized to a wider population of women of reproductive age in Zambia. The evidence generated by this study is important to inform strengthening sexual reproductive health programmes aimed at improving maternal health in Zambia.

Conclusion

The study has established that among WLWH age, marital status and parity were significantly associated with fertility intention. On the contrary, age, place of residence, marital status and wealth quintile were the determinants of fertility intention among mothers living without HIV. HIV status in women of reproductive age is a crucial factor in determining the fertility intentions among women of reproductive age. Understanding diverse factors that determine women’s fertility intentions may be useful in orienting policy towards effective and suitable strategies for contraception, safer conception, and pregnancy planning. Furthermore, strengthening the Prevention of Mother-to-Child Transmission of HIV (PMTCT) health education through family planning clinics and community health workers is important for improving maternal and child health.

Supplemental Material

sj-docx-1-whe-10.1177_17455057231219600 – Supplemental material for Factors associated with fertility intentions among women living with and without human immunodeficiency virus in Zambia

Supplemental material, sj-docx-1-whe-10.1177_17455057231219600 for Factors associated with fertility intentions among women living with and without human immunodeficiency virus in Zambia by David Mulemena, Million Phiri, Namuunda Mutombo, Chinyama Lukama, Julius Nyerere Odhiambo and Chester Kalinda in Women’s Health

Footnotes

The authors are so grateful to the DHS Program for giving us access to the data set used in this study.

Declarations

ORCID iDs

Million Phiri

Chester Kalinda

Supplemental material

Supplemental material for this article is available online.

References

Mosisa

Tsegaye

Wakuma

, et al. Fertility desire and associated factors among people living with HIV in Ethiopia: a systematic review and meta-analysis. Arch Public Health 2020; 78: 123.

Barrow

Jobe

Okonofua

Prevalence and determinants of unmet family planning needs among women of childbearing age in the Gambia: analysis of nationally representative data. Gates Open Res 2021; 4: 124.

Phiri

Lemba

Chomba

, et al. Examining differentials in HIV transmission risk behaviour and its associated factors among men in Southern African countries. Humanit Soc Sci Commun 2022; 9(1): 295–212.

UNAIDS. UNAIDS report on the global AIDS epidemic shows that 2020 targets will not be met because of deeply unequal success; COVID-19 risks blowing HIV progress way off course, https://www.unaids.org/en/resources/presscentre/pressreleaseandstatementarchive/2020/july/20200706_global-aids-report (2020, accessed 26 December 2021).

UNAIDS. 2020 global AIDS update – seizing the moment – tackling entrenched inequalities to end epidemics, https://www.unaids.org/en/resources/documents/2020/global-aids-report (2020, accessed 26 December 2021).

UNAIDS. AIDS statistics – 2019 fact sheet. Geneva: UNAIDS, 2019.

Zambia Statistics Agency Ministry of Health Zambia ICF. Zambia demographic and health survey 2018. Lusaka, Zambia; Rockville, MD: Zambia Statistics Agency Ministry of Health Zambia ICF, 2019.

Bekker

L-G

Alleyne

Baral

, et al. Advancing global health and strengthening the HIV response in the era of the sustainable development goals: the International AIDS Society – Lancet Commission. Lancet Lond Engl 2018; 392: 312–358.

Antiretroviral Therapy Cohort Collaboration. Survival of HIV-positive patients starting antiretroviral therapy between 1996 and 2013: a collaborative analysis of cohort studies. Lancet HIV 2017; 4(8): e349–e356.

10.

Deeks

Lewin

Havlir

DV.

The end of AIDS: HIV infection as a chronic disease. Lancet 2013; 382: 1525–1533.

11.

Deeks

Lewin

Ross

, et al. International AIDS society global scientific strategy: towards an HIV cure 2016. Nat Med 2016; 22(8): 839–850.

12.

Kodzi

Johnson

Casterline

Examining the predictive value of fertility preferences among Ghanaian women. Demogr Res 2010; 22: 965–984.

13.

Adilo

Wordofa

HM.

Prevalence of fertility desire and its associated factors among 15- to 49-year-old people living with HIV/AIDS in Addis Ababa, Ethiopia: a cross-sectional study design. HIV AIDS 2017; 9: 167–176.

14.

Cernigliaro

Barrington

Perez

, et al. Factors related to fertility desire among female sex workers living with HIV in the Dominican Republic. BMC Womens Health 2018; 18: 117.

15.

United Nations, Department of Economic and Social Affairs, Population Division. World family planning 2017- highlights, 2017, https://www.un.org/development/desa/pd/sites/www.un.org.development.desa.pd/files/files/documents/2020/Jan/un_2017_worldfamilyplanning_highlights.pdf

16.

UNAIDS. How women living with HIV will help the world end AIDS. Geneva: UNAIDS, 2012

17.

Vignoli

Rinesi

Fertility plans/intentions. In: Michalos

(ed.) Encyclopedia of quality of life and well-being research. Dordrecht: Springer Netherlands, 2014, pp. 2267–2268.

18.

Zambia Statistics Agency, Ministry of Health (MOH) Zambia, and ICF. Zambia demographic and health survey 2018. Survey report, Zambia Statistics Agency, Ministry of Health, and ICF, Lusaka, Zambia; Rockville, MD, January 2019.

19.

Asfaw

Gashe

FE.

Fertility intentions among HIV positive women aged 18–49 years in Addis Ababa Ethiopia: a cross sectional study. Reprod Health 2014; 11: 36.

20.

Mayhew

Colombini

Kimani

, et al. Fertility intentions and contraceptive practices among clinic-users living with HIV in Kenya: a mixed methods study. BMC Public Health 2017; 17: 626.

21.

Mandell

Rodriguez

Peltzer

, et al. Fertility intentions of women living with HIV and their male partners during the perinatal period in rural South Africa. Int J STD AIDS 2021; 32(8): 740–750.

22.

Phiri

Shasha

Musonda

, et al. Choice of desired family size among young women in Zambia: what matters? J Popul Res 2023; 40: 18.

23.

Bongaarts

Casterline

Fertility transition: is Sub-Saharan Africa Different. Popul Dev Rev 2013; 38(Suppl. 1): 153–168.

24.

Bongaarts

Trends in fertility and fertility preferences in sub-Saharan Africa: the roles of education and family planning programs. Genus 2020; 76: 32.

25.

Phiri

Musonda

Shasha

, et al. Individual and community-level factors associated with early marriage in Zambia: a mixed effect analysis. BMC Womens Health 2023; 23: 21.

26.

Shasha

Phiri

Namayawa

, et al. Prevalence and factors associated with early childbearing in sub-Saharan Africa: evidence from demographic and health surveys of 31 countries. BMC Womens Health 2023; 23: 430.

27.

Mubiana-Mbewe

Bosomprah

Kadota

, et al. Effect of enhanced adherence package on early ART uptake among HIV-positive pregnant women in Zambia: an Individual Randomized Controlled Trial. AIDS Behav 2021; 25(3): 992–1000.

28.

Thomas

Burger

Harper

, et al. Differences in health-related quality of life between HIV-positive and HIV-negative people in Zambia and South Africa: a cross-sectional baseline survey of the HPTN 071 (PopART) trial. Lancet Glob Health 2017; 5(11): e1133–e1141.

29.

Yan

Prevalence and factors associated with fertility desire among people living with HIV: a systematic review and meta-analysis. PLoS ONE 2021; 16(3): e0248872.

30.

Myer

Morroni

Rebe

Prevalence and determinants of fertility intentions of HIV-infected women and men receiving antiretroviral therapy in South Africa. AIDS Patient Care STDS 2007; 21(4): 278–285.

31.

Krashin

Haddad

Tweya

, et al. Factors associated with desired fertility among HIV-positive women and men attending two urban clinics in Lilongwe, Malawi. PLoS ONE 2018; 13(6): e0198798.

32.

Iliyasu

Owen

Aliyu

, et al. ‘I prefer not to have a child than have a HIV-positive child’: a mixed methods study of fertility behaviour of men living with HIV in Northern Nigeria. Int J Behav Med 2020; 27(1): 87–99.

33.

Kaida

Laher

Strathdee

, et al. Childbearing intentions of HIV-positive women of reproductive age in Soweto, South Africa: the influence of expanding access to HAART in an HIV hyperendemic setting. Am J Public Health 2011; 101(2): 350–358.

34.

Marston

Zaba

Eaton

JW.

Relative patterns of sexual activity and fertility among HIV positive and negative women – evidence from 46 DHS. PLoS ONE 2018; 13(10): e0204584.

35.

Kennedy

Serghides

Raboud

, et al. The importance of motherhood in HIV-positive women of reproductive age in Ontario, Canada. AIDS Care 2014; 26(6): 777–784.

36.

Bernardi

Ryser

V-A

Le Goff

J-M.

Gender role-set, family orientations, and women’s fertility intentions in Switzerland. Swiss J Sociol 2013; 39: 9–31.

37.

Busetta

Mendola

Vignoli

Persistent joblessness and fertility intentions. Demogr Res 2019; 40: 185–218.

38.

Testa

MR.

On the positive correlation between education and fertility intentions in Europe: individual- and country-level evidence. Adv Life Course Res 2014; 21: 28–42.

39.

Londero

Rossetti

Pittini

, et al. Maternal age and the risk of adverse pregnancy outcomes: a retrospective cohort study. BMC Pregnancy Childbirth 2019; 19: 1–10.

40.

Jacobsson

Ladfors

Milsom

Advanced maternal age and adverse perinatal outcome. Obstet Gynecol 2004; 104: 727–733.

41.

Carolan

Frankowska

Advanced maternal age and adverse perinatal outcome: a review of the evidence. Midwifery 2011; 27(6): 793–801.

42.

Song

Grilo

Mathur

, et al. Differential Impacts of HIV status on short-term fertility desires among couples in Rakai, Uganda. PLoS ONE 2019; 14(1): e0210935.

43.

Bongaarts

Cleland

Townsend

, et al. Family planning programs for the 21st century: rationale and design. New York: Population Council, 2012.

44.

Mubita-Ngoma

Kadantu

MC.

Knowledge and use of modern family planning methods by rural women in Zambia: research article. Curationis 2010; 33: 17–22.

45.

Etokidem

Ndifon

Etowa

, et al. Family planning practices of rural community dwellers in cross River State, Nigeria. Niger J Clin Pract 2017; 20(6): 707–715.

46.

Komasawa

Yuasa

Shirayama

, et al. Demand for family planning satisfied with modern methods and its associated factors among married women of reproductive age in rural Jordan: a cross-sectional study. PLoS ONE 2020; 15(3): e0230421.

47.

Hailemariam

Haddis

Factors affecting unmet need for family planning in southern nations, nationalities and peoples region, Ethiopia. Ethiop J Health Sci 2011; 21(2): 77–89.

48.

Ahinkorah

Seidu

Budu

, et al. Which factors predict fertility intentions of married men and women? Results from the 2012 Niger Demographic and Health Survey. PLoS ONE 2021; 16(6): e0252281.

49.

Ewemooje

Biney

Amoateng

, et al. Fertility timing preferences among women of reproductive age: the case of Malawi and South Africa. South Afr J Demogr 2021; 21: 27–68.

50.

United Nations. The sustainable development goals report 2022. New York: United Nations, 2022, https://unstats.un.org/sdgs/report/2022/

51.

World Health Organization. World Health Statistics 2018: monitoring health for the SDGs, sustainable development goals. Geneva: World Health Organization, 2018.

52.

Vrazo

Sullivan

Phelps

BR.

Eliminating mother-to-child transmission of HIV by 2030: 5 strategies to ensure continued progress. Glob Health Sci Pract 2018; 6: 249–256.

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

0.03 MB