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'Kusvika taparadzaniswa nerufu' (Until death do us part) N Spark-du Preez , B Zaba , C Nyamukapa , M Mlilo & S Gregson Published online: 11 Nov 2009.
To cite this article: N Spark-du Preez , B Zaba , C Nyamukapa , M Mlilo & S Gregson (2004) 'Kusvika taparadzaniswa nerufu' (Until death do us part), African Journal of AIDS Research, 3:1, 81-91, DOI: 10.2989/16085900409490321 To link to this article: http://dx.doi.org/10.2989/16085900409490321
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African Journal of AIDS Research 2004, 3(1): 81–91 Printed in South Africa — All rights reserved
AJAR ISSN 1608–5906
‘Kusvika taparadzaniswa nerufu’ (Until death do us part) N Spark-du Preez1*, B Zaba2, C Nyamukapa3, M Mlilo3 and S Gregson3,4 Human Sciences Department, Loughborough University, Leicestershire, LE11 3TU, United Kingdom Centre for Population Studies, London School of Hygiene and Tropical Medicine, London University, 49–51 Bedford Square, London WC1B 3DP, United Kingdom 3 Biomedical Research and Training Institute, University of Zimbabwe Campus, PO Box CY1753, Causeway, Harare, Zimbabwe 4 Department of Infectious Disease Epidemiology, Imperial College Faculty of Medicine, University of London, Norfolk Place, London W2 1PG, United Kingdom * Corresponding author, e-mail: [email protected] 1
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A cross-sectional study of 7 667 non-virgins between 15 and 54 years of age was carried out to assess the protective effect of marriage against HIV acquisition in a rural population in Zimbabwe, whilst taking into account gender-differentials in risk factors for seroconversion. Persons in stable first marriages and long-term consensual cohabiting unions had higher odds of HIV infection than never-married people but a lower risk than those who had been divorced or widowed, even after adjusting for known confounders and significant risk factors for infection. Partner-related risk factors appear to play a more pivotal role in determining HIV prevalence in females than for males, for whom personal sexual behaviour risk factors are more dominant. Keywords: HIV, marital status, rural, Zimbabwe
Introduction It has been found that persons in stable long-term relationships — i.e. married or cohabiting longer than 12 months — have lower HIV prevalence than divorcees and widows of the same age (Rwandan HIV Seroprevalence Study Group, 1989; Lindan, Allen & Caraël, 1991; Caraël, 1994; Ntozi, 1997; Twa-Twa, Nakanaabi & Sekimpi, 1997). However, the higher prevalence found amongst divorcees and widows may in part be a consequence of experiences at and during marriage rather than entirely the consequence of riskier behaviour amongst unmarried individuals. The aim of this study is to examine the contribution that a person’s marital status makes to HIV transmission in Manicaland Province, Zimbabwe, whilst taking into account gender-differentials in risk factors for seroconversion. Recent literature regarding nuptiality and HIV has focused on the number of premarital partners as a risk factor for seroconversion (Bracher, Santow & Cotts Watkins, 2002) in which the new spouse may already be infected on entry into marriage as a result of casual partners before a first marriage, as well as marital partners from a previous marriage. If uninfected, marriage should therefore prevent the acquisition of HIV in contrast to the promiscuity of ‘moving around’ (Whyte, 1997; Setel, 1999) so long as both partners are monogamously faithful. Microsimulation models of HIV transmission in other patrilineal African societies (Bracher et al., 2002), however, have suggested that early marriage may not be protective, particularly if this also implies earlier initiation of extramarital sex or earlier contact
with older men who have had multiple pre-marital relationships. In the absence of hard data, these modelling results suggested that marriage was less protective for men because their exposure time before first marriage was longer than for women. In a rural Tanzanian study, HIV prevalence in men aged 30+ was higher amongst those who had never married and those divorced or widowed, compared with those currently married (Quigley, Munguti, Grosskurth, Todd, Mosha, Senkoro, Newell, Mayaud, KaGina, Klokke, Mabey, Gavyole & Hayes, 1997). In this case, as with the model estimates, marriage would not offer the same degree of protection for any older never-married male deciding to marry, as it would have done at younger ages with lower HIV prevalence amongst those never married. Multiple marriages, whether monogamous or polygamous, have also been linked to greater risk of HIV transmission (Larsen, 1989; Caraël, 1994; Adeokun & Nalwadda, 1997; Carpenter, Kamali, Ruberantwari, Malamba & Whitworth, 1999). Where separation, divorce and widowhood lead to new partnership formation, numbers of lifetime partners increase, thereby raising the risk of HIV infection (Caraël, Van de Perre & Lepage, 1988; Quigley et al., 1997). Indeed, higher HIV prevalence amongst female divorcees and widows than amongst those married and never-married has been attributed to their having higher numbers of lifetime sexual partners (Barongo, Borgdorff, Mosha, Nicoll, Grosskurth, Senkoro, Newell, Changalucha, Klokke, Killewo, Velema, Hayes, Dunn, Muller & Rugemalila, 1992), although
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it also increases the likelihood of widowhood as well as divorce. The increased mortality associated with HIV/AIDS can act as a catalyst with respect to remarriage, if traditional norms are observed. Widowed or divorced males take on younger brides and brother-in-laws may ‘inherit’ their dead brothers’ widows through the levirate. In the latter case, the widow continues to conceive children in the name of the dead husband (Drew, Foster & Chitima, 1996). This is particularly significant in those patrilineal societies where polygyny is common, and widows and divorcees report higher HIV prevalence than those who are never-married or married (Lindan et al., 1991; Barongo et al., 1992; Ntozi, 1997). In this context, widowhood — with its associated high-risk practices such as sexual cleansing and the levirate — is a risk factor for both the inherited widow and the brother-in-law. Emphasis in this paper, however, is on the female disadvantage in a patriarchal society wherein free remarriage for widows is a rarer occurrence than for widowers (Owen, 2000). In certain high fertility societies where post-partum sexual abstinence is common practice, men in polygynous unions have been found to be less likely to have extramarital sex than men in monogamous unions (Caldwell & Caldwell, 1993; Gregson, Anderson, Ndlovu, Zhuwau & Chandiwana, 1998). In contrast, it is women in polygynous unions who tend to seek partners outside the marriage more so than women in monogamous unions (Orubuloye, Caldwell & Caldwell, 1991; Twa-Twa et al., 1997; Nnko, Boerma, Urassa, Mwaluko & Zaba, 2004). This paper investigates marital status as a risk factor for HIV transmission through a case study in a rural area of Zimbabwe where marriage is almost universal (CSO ZDHS, 2000). The median age at first marriage for Zimbabwean women is 19.7 years, while men enter into marriage five years later on average (CSO ZDHS, 2000). The median age at first sexual intercourse for Zimbabwean women (19.1 years) is close to their median age at first marriage, although this varies by residence and education (CSO ZDHS, 2000). Although the median age at first sex for men is just 12 months later than women, there is a sizeable delay before their first marriage. The Shona and Ndebele, Zimbabwe’s two main ethnic groups, follow a patrilineal, extended family system (Bourdillon, 1993) with patrilocal exogamous marriage customs (Meekers, 1994). There are three types of marriage in Zimbabwe: the civil marriage, the registered customary marriage and the unregistered customary law union. Civil marriage either takes place in a church, at a religious gathering or in a magistrate’s court and is registered. These are more common among younger, urban, more educated and economically independent Zimbabweans (Meekers, 1994). The customary marriage union is only available to black Zimbabweans and is solemnised by a magistrate in a community court. In this type of union, a man is permitted to marry more than one woman (CRLP, 1997) and a woman cannot sue for adultery as the husband’s lover may be one of his other wives (Mavhunga, 2003). It is estimated that one in six currently married women in Zimbabwe are in a polygynous union (CSO ZDHS, 2000), with the average polygynous union comprising 2.3 wives (CRLP, 2001). This proportion of women in a polygynous union varies according to their residence and education. Even if polygyny is not an accepted
Spark-du Preez, Zaba, Nyamukapa, Mlilo and Gregson
practice, a man might maintain a second younger or more fertile ‘unofficial wife’ in a separate household (Bourdillon, 1993). An unregistered customary law union or ‘roora’ marriage is a long process which usually begins with small personal objects known as ‘love tokens’ being exchanged by the couple (Meekers, 1994). The prospective groom and his family then begin the bridewealth (lobola) payments which can be paid in instalments over several years. All African marriages in Zimbabwe, whether they be civil or customary, are preceded by this custom. Societies that have this form of bridewealth system and financial interests in marriage tend to prize premarital virginity (Obbo, 1980); however, by the time enough money has been raised, premarital sex has usually already occurred (Bourdillon, 1993). Should the couple wish to separate, no divorce proceedings are needed, unlike the previous two types of marriages. Following the death of a spouse, a widow is expected to remarry within the family or risk losing her children and property. Since 1997, the law governing the inheritance under customary law has changed in favour of the widow. However, a widow’s situation will also depend on her education, age, residence, relationship with her husband’s family, the economic and social status of relatives on both sides, as well as whether the brother-in-law wishes to ‘inherit’ her (Owen, 2000). In 1999, 87% of widowed persons were women (CSO ZDHS, 2000). Contributing factors have been lower life expectancy for men and the large age disparities in marital unions. Furthermore, in a society where polygyny is practiced, a man’s marital status does not necessarily change if a wife dies or if he divorces. In 1999, 7% of females and 3.1% of males were divorced (CSO ZDHS, 2000). Contrary to the ideology of the bridewealth payment, many men believe this gives them ‘ownership’ rights over their wives, (ZHR, 2001) and this therefore influences relative power within a married couple’s sexual relationship. Men usually have control over the initiation of sex, condom use and their wife’s fertility (Kesby, 2000). Lack of communication about sexual matters in stable relationships is also known to be a barrier to HIV prevention (Gupta & Weiss, 1993). A woman may be labelled a ‘prostitute’ if she openly discusses sexual issues (Maposhera, 1996, in Loewenson, Edwards & Ndlovu-Hove, 1996) or if she requests that her partner or husband wear a condom or if she initiates sexual intercourse — the finger of suspicion is pointed at her (Kesby, 2000). In a pilot study in two rural areas in Zimbabwe, Kesby (2000) found that forced sex with a drunken husband was a common theme. If women refused to try new sexual positions or practices such as dry sex or chikapa (‘sexual acrobatics’), their husbands saw these refusals as justification for seeking more willing partners outside marriage (Kesby, 2000) . However, it is also considered increasingly common for married women in such relationships to seek more loving and fulfilling partnerships outside marriage where the power imbalance is altered (McGrath, Rwabukwali, Schumann, Pearson-Marks, Nakayiwa, Namande, Nakyobe & Mukasa, 1993; Kesby, 2000). In the same way, mapoto unions, where the couple live together, despite no legal recognition, confer much greater freedom on the women involved than do formal marriages where bridewealth has to be paid (Bourdillion, 1987; ZHR, 2001).
African Journal of AIDS Research 2004, 3: 81–91
Another common reason for a woman seeking a partner outside marriage is if her husband cannot provide for her financially or if she seeks revenge for his infidelity (McGrath et al., 1993). The man is therefore not the sole perpetrator of extramarital affairs, it is just more accepted that he can have partners outside marriage (McGrath et al., 1993). In a patrilineal society with marriage customs as described above, we would not expect marriage to guarantee protection against HIV acquisition.
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Materials and Methods Study area This paper utilises baseline data taken from an ongoing longitudinal population-based HIV/STI prevention project in the Manicaland Province in Zimbabwe (Gregson, Mason, Garnett, Zhuwau, Nyamukapa, Anderson & Chandiwana, 2001). Between 1998 and 2000, locally resident males aged 17–54 years and females aged 15–44 years were identified in a preliminary household survey, and a total of 9 843 (80% of those eligible) agreed to participate in the project (Gregson, Nyamukapa, Garnett, Mason, Zhuwau, Caraël, Chandiwana & Anderson, 2002a). Written informed consent was obtained and participants were offered free voluntary HIV counselling and testing. Dried blood-spot samples were collected for HIV testing using a dipstick-dot immunoassay with high specificity and sensitivity (99.6%) (Ray, Mason, Smith, Rogers, Tobaiwa & Katzenstein, 1997). Of the 9 450 participants who had age data available, 66% lived on large-scale commercial estates and in subsistence farming areas, while the remainder lived in small towns and roadside trading centres. Further details about the original study design can be found in Gregson et al. (2002a). ‘Virgins’ (i.e. those who had not yet had penetrative vaginal intercourse) were excluded from the analysis presented in this paper since they are an unexposed group, reducing the sample size from 9 450 to 7 797 individuals, 54% of whom were female. Of these ‘virgins’, 70% lived on large-scale commercial estates and in subsistence farming areas, while the remainder lived in small towns and roadside trading centres. In order to create more mutually exclusive marital status categories, a further 130 individuals were excluded from secondary analysis. These included: 19 people who reported that they were currently widowed but had also been divorced for longer than two years; 60 people who reported that they were currently widowed but had also been divorced in the last two years; 19 people who reported being currently divorced or separated and had also been widowed in the last two years; 42 people who reported being currently divorced or separated but had also been widowed in the last two years. Although results were not significantly different after removing these 130 people, results are reported without them for the sake of clarity, bringing the final sample size down to 7 667. Sexual behaviour data is particularly prone to recall, social desirability and participation bias (Gregson et al., 2002a). Several steps were taken to reduce this, such as the use of confidential ‘voting’ to reduce social desirability bias (Gregson, Zhuwau, Ndlovu & Nyamukapa, 2002b); however, some residual bias remains. Thirteen people, for example,
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reported having one lifetime partner despite having had 6+ partners before marriage. These particular inconsistencies probably follow from the use of the confidential ‘voting’ in which errors made by respondents when completing the ‘voting’ slips could not be detected by the enumerators. According to Ghani and Garnett (2000), the best predictors of HIV status in an established epidemic are those which span longest periods of sexual history, such as age at first sex and number of lifetime partners. Consistency checks were therefore carried out on sexual behaviour variables using the two variables ‘number of lifetime partners’ and ‘age at first sex’. This meant that about 3% of the ‘virgins’ identified using ‘age at first sex’ and double-checked using ‘number of lifetime partners’ who were excluded from the study reported sexual activity through other sexual behaviour variables. A person’s ‘position location’ in the sexual network is a good predictor of their HIV status (Gregson et al., 2002a). Such variables describe how close the person is to those who have very high numbers of partners. In the present study this information is not measured directly, but in describing the last two sexual partners in the last month. The respondent is asked whether they thought these partners sometimes had sex with others. In addition, they report whether their current partner is a regular partner (one year +) and whether their current partner visited bars or beer halls. These indicators are used as proxies of the degree of risk posed by these recent partners. Unfortunately no information is available on whether currently married women are in a polygynous union. Statistical methods The following marital status categories were used in this study: never-married, married or cohabiting 12 months or more (first marriage), widowed less than two years, widowed longer than two years, divorced or separated less than two years, divorced or separated longer than two years, married but widowed in the last two years (MPW), and married but divorced in the last two years (MPD). Those who reported being married could not be separated from those who were simply cohabiting for longer than 12 months as no distinction was made in the questionnaire design. Their experiences may be slightly different because of different social constraints placed upon the relationship; however, the main social construct of interest is stability within a union. In the final regression models, the terms ‘ever-widowed’ and ‘everdivorced’ are used to refer to all those who had ever experienced these events, regardless of their current marital status, given that their experiences are similar. For this reason, those who reported being currently married but had experienced a divorce or spouse’s death in the previous two years were included in either the ‘ever-divorced’ or ‘ever-widowed’ groups as they had experienced a transition from a stable union to its breakdown. Table 1 describes how the different categories of marital status were derived. For the investigation of the relationship between HIV prevalence and marital status, possible explanatory variables relating to the sociodemographic, behavioural and spatial mobility characteristics of participants and their partners were chosen on the basis of findings from earlier studies.
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Spark-du Preez, Zaba, Nyamukapa, Mlilo and Gregson
Table 1: Categorisation of marital status Current marital status Never married Currently married
Widowed
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Divorced or separated
Previous marital status change None None Divorced in last 2 years Widowed in last 2 years None Widowed in last 2 years None Divorced in last 2 years
(n) (1 925) (3 883) (673) (105) (44) (310) (56) (671)
Since sex and age are important confounders in the relationship between marital status and HIV prevalence, firstly bivariate models stratified by sex and controlling for age alone were constructed for each measure in order to identify a subset of variables to consider for subsequent analysis. Logistic regression models were then developed to examine the combined effects of age, marital status and each of the other variables on HIV status. An extensive table of HIV prevalence and age and marital status-adjusted odds ratios for HIV infection among men and women by socio-demographic, behavioural and partner-related variables is available on request. Finally, sex-specific multivariate models were generated to compare the odds of being HIV-positive in each marital status group, after controlling for possible confounders and effect modifiers. Any differences in category coding of variables between males and females reflect observed differentials in HIV prevalence after adjusting for age and marital status. Due to the large number of parameters estimated in the preliminary models, variables that were not significantly associated with the outcome variable (P ≤ 0.05) after controlling for age and marital status were not tested in the multivariate regression models in the interests of parsimony. The order in which variables were removed from the model was determined by their position on the causal pathway (more distant variables were removed first) and the strength of their association with the outcome. The conceptual framework used to determine these relationships is illustrated in Figure 1. Univariate and bivariate data analyses were performed using Stata 7.0 (Stata Co-operation, College Station, Texas, USA) and 95% confidence intervals and P-values were computed for all variables. The Pearson Chi squared test was used to test for differences in HIV prevalence by sociodemographic, sexual behaviour, spatial mobility and partnerrelated characteristics separately for males and females and the significance of each parameter was tested using the Wald statistic. A Receiver Operating Curve (ROC) was used to evaluate the predicted accuracy of the final models. In this case the predicted values generated by the logistic model can be viewed as a continuous indicator to be compared to the observed binary response variable. The area under the curve measures discrimination, i.e. the ability of the test to correctly classify those with and without the outcome. The measure will vary between 0.5 and 1. An area of 0.5 represents the diagonal, attained when no discrimination exists or by chance alone. An area of 1 represents the perfect indicator.
Label Never married Currently married Married previously divorced (MPD) Married previously widowed (MPW) Long-term widow Recently widowed Long-term divorcee Recently divorced
Final category Never married First marriage Ever-divorced Ever-widowed Ever-widowed Ever-widowed Ever-divorced Ever-divorced
Results Univariate and bivariate analyses Sixty per cent of females were currently married or in a cohabiting or long-term relationship (12 months or more) and only 8% were never-married. In contrast, the largest category for males was the never-married group (44%) with 40% being currently married. More female than male respondents were currently divorced/separated (14% vs 5%, respectively) and currently widowed (8% vs 1.1%). These differences partly reflect differences in the age-ranges and distributions between men and women in the study. Similar proportions of men and women who were either divorced or widowed in the two years prior to the study had remarried in this sample (approximately 9% and 1.5% respectively in each case). Whilst the majority of females (59%) married between the ages of 15 and 19, the highest proportion of males (25%) married after age 25. Table 2 presents sex-stratified HIV prevalence by age group and marital status, and age-adjusted odds ratios for HIV infection by marital status. HIV prevalence among male and female study participants who reported having started sexual activity was 22.5% and 30.1%, respectively. HIV prevalence peaks at 46% at ages 30–34 for males and at 40% at ages 25–29 for females. HIV prevalence was highest in the least stable marital status groups. After adjusting for age, being married had a protective effect relative to being never-married for females but the opposite was true for males. Ever-married men and women had similar levels of HIV prevalence but a large sex-differential exists amongst the never-married. For males, the crude odds of being HIVpositive were significantly higher if the individual had been married compared to never having married, whereas for females there was no statistically significant difference between the between the never- and ever-married groups. Roughly 18% of the study group were either currently divorced or separated or had had a divorce in the two years prior to the survey. The equivalent percentage for widowhood was 6%. More women than men reported recent divorce or widowhood. Recent experience of divorce and widowhood were each significantly associated with being HIV-positive (χ2, P < 0.001) for both sexes at all ages as opposed to being never-married, with the exception of the youngest age group (
African Journal of AIDS Research Publication details, including instructions for authors and subscription information: http://www.tandfonline.com/loi/raar20
'Kusvika taparadzaniswa nerufu' (Until death do us part) N Spark-du Preez , B Zaba , C Nyamukapa , M Mlilo & S Gregson Published online: 11 Nov 2009.
To cite this article: N Spark-du Preez , B Zaba , C Nyamukapa , M Mlilo & S Gregson (2004) 'Kusvika taparadzaniswa nerufu' (Until death do us part), African Journal of AIDS Research, 3:1, 81-91, DOI: 10.2989/16085900409490321 To link to this article: http://dx.doi.org/10.2989/16085900409490321
PLEASE SCROLL DOWN FOR ARTICLE Taylor & Francis makes every effort to ensure the accuracy of all the information (the “Content”) contained in the publications on our platform. However, Taylor & Francis, our agents, and our licensors make no representations or warranties whatsoever as to the accuracy, completeness, or suitability for any purpose of the Content. Any opinions and views expressed in this publication are the opinions and views of the authors, and are not the views of or endorsed by Taylor & Francis. The accuracy of the Content should not be relied upon and should be independently verified with primary sources of information. Taylor and Francis shall not be liable for any losses, actions, claims, proceedings, demands, costs, expenses, damages, and other liabilities whatsoever or howsoever caused arising directly or indirectly in connection with, in relation to or arising out of the use of the Content. This article may be used for research, teaching, and private study purposes. Any substantial or systematic reproduction, redistribution, reselling, loan, sub-licensing, systematic supply, or distribution in any form to anyone is expressly forbidden. Terms & Conditions of access and use can be found at http:// www.tandfonline.com/page/terms-and-conditions
Copyright © NISC Pty Ltd
African Journal of AIDS Research 2004, 3(1): 81–91 Printed in South Africa — All rights reserved
AJAR ISSN 1608–5906
‘Kusvika taparadzaniswa nerufu’ (Until death do us part) N Spark-du Preez1*, B Zaba2, C Nyamukapa3, M Mlilo3 and S Gregson3,4 Human Sciences Department, Loughborough University, Leicestershire, LE11 3TU, United Kingdom Centre for Population Studies, London School of Hygiene and Tropical Medicine, London University, 49–51 Bedford Square, London WC1B 3DP, United Kingdom 3 Biomedical Research and Training Institute, University of Zimbabwe Campus, PO Box CY1753, Causeway, Harare, Zimbabwe 4 Department of Infectious Disease Epidemiology, Imperial College Faculty of Medicine, University of London, Norfolk Place, London W2 1PG, United Kingdom * Corresponding author, e-mail: [email protected] 1
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A cross-sectional study of 7 667 non-virgins between 15 and 54 years of age was carried out to assess the protective effect of marriage against HIV acquisition in a rural population in Zimbabwe, whilst taking into account gender-differentials in risk factors for seroconversion. Persons in stable first marriages and long-term consensual cohabiting unions had higher odds of HIV infection than never-married people but a lower risk than those who had been divorced or widowed, even after adjusting for known confounders and significant risk factors for infection. Partner-related risk factors appear to play a more pivotal role in determining HIV prevalence in females than for males, for whom personal sexual behaviour risk factors are more dominant. Keywords: HIV, marital status, rural, Zimbabwe
Introduction It has been found that persons in stable long-term relationships — i.e. married or cohabiting longer than 12 months — have lower HIV prevalence than divorcees and widows of the same age (Rwandan HIV Seroprevalence Study Group, 1989; Lindan, Allen & Caraël, 1991; Caraël, 1994; Ntozi, 1997; Twa-Twa, Nakanaabi & Sekimpi, 1997). However, the higher prevalence found amongst divorcees and widows may in part be a consequence of experiences at and during marriage rather than entirely the consequence of riskier behaviour amongst unmarried individuals. The aim of this study is to examine the contribution that a person’s marital status makes to HIV transmission in Manicaland Province, Zimbabwe, whilst taking into account gender-differentials in risk factors for seroconversion. Recent literature regarding nuptiality and HIV has focused on the number of premarital partners as a risk factor for seroconversion (Bracher, Santow & Cotts Watkins, 2002) in which the new spouse may already be infected on entry into marriage as a result of casual partners before a first marriage, as well as marital partners from a previous marriage. If uninfected, marriage should therefore prevent the acquisition of HIV in contrast to the promiscuity of ‘moving around’ (Whyte, 1997; Setel, 1999) so long as both partners are monogamously faithful. Microsimulation models of HIV transmission in other patrilineal African societies (Bracher et al., 2002), however, have suggested that early marriage may not be protective, particularly if this also implies earlier initiation of extramarital sex or earlier contact
with older men who have had multiple pre-marital relationships. In the absence of hard data, these modelling results suggested that marriage was less protective for men because their exposure time before first marriage was longer than for women. In a rural Tanzanian study, HIV prevalence in men aged 30+ was higher amongst those who had never married and those divorced or widowed, compared with those currently married (Quigley, Munguti, Grosskurth, Todd, Mosha, Senkoro, Newell, Mayaud, KaGina, Klokke, Mabey, Gavyole & Hayes, 1997). In this case, as with the model estimates, marriage would not offer the same degree of protection for any older never-married male deciding to marry, as it would have done at younger ages with lower HIV prevalence amongst those never married. Multiple marriages, whether monogamous or polygamous, have also been linked to greater risk of HIV transmission (Larsen, 1989; Caraël, 1994; Adeokun & Nalwadda, 1997; Carpenter, Kamali, Ruberantwari, Malamba & Whitworth, 1999). Where separation, divorce and widowhood lead to new partnership formation, numbers of lifetime partners increase, thereby raising the risk of HIV infection (Caraël, Van de Perre & Lepage, 1988; Quigley et al., 1997). Indeed, higher HIV prevalence amongst female divorcees and widows than amongst those married and never-married has been attributed to their having higher numbers of lifetime sexual partners (Barongo, Borgdorff, Mosha, Nicoll, Grosskurth, Senkoro, Newell, Changalucha, Klokke, Killewo, Velema, Hayes, Dunn, Muller & Rugemalila, 1992), although
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it also increases the likelihood of widowhood as well as divorce. The increased mortality associated with HIV/AIDS can act as a catalyst with respect to remarriage, if traditional norms are observed. Widowed or divorced males take on younger brides and brother-in-laws may ‘inherit’ their dead brothers’ widows through the levirate. In the latter case, the widow continues to conceive children in the name of the dead husband (Drew, Foster & Chitima, 1996). This is particularly significant in those patrilineal societies where polygyny is common, and widows and divorcees report higher HIV prevalence than those who are never-married or married (Lindan et al., 1991; Barongo et al., 1992; Ntozi, 1997). In this context, widowhood — with its associated high-risk practices such as sexual cleansing and the levirate — is a risk factor for both the inherited widow and the brother-in-law. Emphasis in this paper, however, is on the female disadvantage in a patriarchal society wherein free remarriage for widows is a rarer occurrence than for widowers (Owen, 2000). In certain high fertility societies where post-partum sexual abstinence is common practice, men in polygynous unions have been found to be less likely to have extramarital sex than men in monogamous unions (Caldwell & Caldwell, 1993; Gregson, Anderson, Ndlovu, Zhuwau & Chandiwana, 1998). In contrast, it is women in polygynous unions who tend to seek partners outside the marriage more so than women in monogamous unions (Orubuloye, Caldwell & Caldwell, 1991; Twa-Twa et al., 1997; Nnko, Boerma, Urassa, Mwaluko & Zaba, 2004). This paper investigates marital status as a risk factor for HIV transmission through a case study in a rural area of Zimbabwe where marriage is almost universal (CSO ZDHS, 2000). The median age at first marriage for Zimbabwean women is 19.7 years, while men enter into marriage five years later on average (CSO ZDHS, 2000). The median age at first sexual intercourse for Zimbabwean women (19.1 years) is close to their median age at first marriage, although this varies by residence and education (CSO ZDHS, 2000). Although the median age at first sex for men is just 12 months later than women, there is a sizeable delay before their first marriage. The Shona and Ndebele, Zimbabwe’s two main ethnic groups, follow a patrilineal, extended family system (Bourdillon, 1993) with patrilocal exogamous marriage customs (Meekers, 1994). There are three types of marriage in Zimbabwe: the civil marriage, the registered customary marriage and the unregistered customary law union. Civil marriage either takes place in a church, at a religious gathering or in a magistrate’s court and is registered. These are more common among younger, urban, more educated and economically independent Zimbabweans (Meekers, 1994). The customary marriage union is only available to black Zimbabweans and is solemnised by a magistrate in a community court. In this type of union, a man is permitted to marry more than one woman (CRLP, 1997) and a woman cannot sue for adultery as the husband’s lover may be one of his other wives (Mavhunga, 2003). It is estimated that one in six currently married women in Zimbabwe are in a polygynous union (CSO ZDHS, 2000), with the average polygynous union comprising 2.3 wives (CRLP, 2001). This proportion of women in a polygynous union varies according to their residence and education. Even if polygyny is not an accepted
Spark-du Preez, Zaba, Nyamukapa, Mlilo and Gregson
practice, a man might maintain a second younger or more fertile ‘unofficial wife’ in a separate household (Bourdillon, 1993). An unregistered customary law union or ‘roora’ marriage is a long process which usually begins with small personal objects known as ‘love tokens’ being exchanged by the couple (Meekers, 1994). The prospective groom and his family then begin the bridewealth (lobola) payments which can be paid in instalments over several years. All African marriages in Zimbabwe, whether they be civil or customary, are preceded by this custom. Societies that have this form of bridewealth system and financial interests in marriage tend to prize premarital virginity (Obbo, 1980); however, by the time enough money has been raised, premarital sex has usually already occurred (Bourdillon, 1993). Should the couple wish to separate, no divorce proceedings are needed, unlike the previous two types of marriages. Following the death of a spouse, a widow is expected to remarry within the family or risk losing her children and property. Since 1997, the law governing the inheritance under customary law has changed in favour of the widow. However, a widow’s situation will also depend on her education, age, residence, relationship with her husband’s family, the economic and social status of relatives on both sides, as well as whether the brother-in-law wishes to ‘inherit’ her (Owen, 2000). In 1999, 87% of widowed persons were women (CSO ZDHS, 2000). Contributing factors have been lower life expectancy for men and the large age disparities in marital unions. Furthermore, in a society where polygyny is practiced, a man’s marital status does not necessarily change if a wife dies or if he divorces. In 1999, 7% of females and 3.1% of males were divorced (CSO ZDHS, 2000). Contrary to the ideology of the bridewealth payment, many men believe this gives them ‘ownership’ rights over their wives, (ZHR, 2001) and this therefore influences relative power within a married couple’s sexual relationship. Men usually have control over the initiation of sex, condom use and their wife’s fertility (Kesby, 2000). Lack of communication about sexual matters in stable relationships is also known to be a barrier to HIV prevention (Gupta & Weiss, 1993). A woman may be labelled a ‘prostitute’ if she openly discusses sexual issues (Maposhera, 1996, in Loewenson, Edwards & Ndlovu-Hove, 1996) or if she requests that her partner or husband wear a condom or if she initiates sexual intercourse — the finger of suspicion is pointed at her (Kesby, 2000). In a pilot study in two rural areas in Zimbabwe, Kesby (2000) found that forced sex with a drunken husband was a common theme. If women refused to try new sexual positions or practices such as dry sex or chikapa (‘sexual acrobatics’), their husbands saw these refusals as justification for seeking more willing partners outside marriage (Kesby, 2000) . However, it is also considered increasingly common for married women in such relationships to seek more loving and fulfilling partnerships outside marriage where the power imbalance is altered (McGrath, Rwabukwali, Schumann, Pearson-Marks, Nakayiwa, Namande, Nakyobe & Mukasa, 1993; Kesby, 2000). In the same way, mapoto unions, where the couple live together, despite no legal recognition, confer much greater freedom on the women involved than do formal marriages where bridewealth has to be paid (Bourdillion, 1987; ZHR, 2001).
African Journal of AIDS Research 2004, 3: 81–91
Another common reason for a woman seeking a partner outside marriage is if her husband cannot provide for her financially or if she seeks revenge for his infidelity (McGrath et al., 1993). The man is therefore not the sole perpetrator of extramarital affairs, it is just more accepted that he can have partners outside marriage (McGrath et al., 1993). In a patrilineal society with marriage customs as described above, we would not expect marriage to guarantee protection against HIV acquisition.
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Materials and Methods Study area This paper utilises baseline data taken from an ongoing longitudinal population-based HIV/STI prevention project in the Manicaland Province in Zimbabwe (Gregson, Mason, Garnett, Zhuwau, Nyamukapa, Anderson & Chandiwana, 2001). Between 1998 and 2000, locally resident males aged 17–54 years and females aged 15–44 years were identified in a preliminary household survey, and a total of 9 843 (80% of those eligible) agreed to participate in the project (Gregson, Nyamukapa, Garnett, Mason, Zhuwau, Caraël, Chandiwana & Anderson, 2002a). Written informed consent was obtained and participants were offered free voluntary HIV counselling and testing. Dried blood-spot samples were collected for HIV testing using a dipstick-dot immunoassay with high specificity and sensitivity (99.6%) (Ray, Mason, Smith, Rogers, Tobaiwa & Katzenstein, 1997). Of the 9 450 participants who had age data available, 66% lived on large-scale commercial estates and in subsistence farming areas, while the remainder lived in small towns and roadside trading centres. Further details about the original study design can be found in Gregson et al. (2002a). ‘Virgins’ (i.e. those who had not yet had penetrative vaginal intercourse) were excluded from the analysis presented in this paper since they are an unexposed group, reducing the sample size from 9 450 to 7 797 individuals, 54% of whom were female. Of these ‘virgins’, 70% lived on large-scale commercial estates and in subsistence farming areas, while the remainder lived in small towns and roadside trading centres. In order to create more mutually exclusive marital status categories, a further 130 individuals were excluded from secondary analysis. These included: 19 people who reported that they were currently widowed but had also been divorced for longer than two years; 60 people who reported that they were currently widowed but had also been divorced in the last two years; 19 people who reported being currently divorced or separated and had also been widowed in the last two years; 42 people who reported being currently divorced or separated but had also been widowed in the last two years. Although results were not significantly different after removing these 130 people, results are reported without them for the sake of clarity, bringing the final sample size down to 7 667. Sexual behaviour data is particularly prone to recall, social desirability and participation bias (Gregson et al., 2002a). Several steps were taken to reduce this, such as the use of confidential ‘voting’ to reduce social desirability bias (Gregson, Zhuwau, Ndlovu & Nyamukapa, 2002b); however, some residual bias remains. Thirteen people, for example,
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reported having one lifetime partner despite having had 6+ partners before marriage. These particular inconsistencies probably follow from the use of the confidential ‘voting’ in which errors made by respondents when completing the ‘voting’ slips could not be detected by the enumerators. According to Ghani and Garnett (2000), the best predictors of HIV status in an established epidemic are those which span longest periods of sexual history, such as age at first sex and number of lifetime partners. Consistency checks were therefore carried out on sexual behaviour variables using the two variables ‘number of lifetime partners’ and ‘age at first sex’. This meant that about 3% of the ‘virgins’ identified using ‘age at first sex’ and double-checked using ‘number of lifetime partners’ who were excluded from the study reported sexual activity through other sexual behaviour variables. A person’s ‘position location’ in the sexual network is a good predictor of their HIV status (Gregson et al., 2002a). Such variables describe how close the person is to those who have very high numbers of partners. In the present study this information is not measured directly, but in describing the last two sexual partners in the last month. The respondent is asked whether they thought these partners sometimes had sex with others. In addition, they report whether their current partner is a regular partner (one year +) and whether their current partner visited bars or beer halls. These indicators are used as proxies of the degree of risk posed by these recent partners. Unfortunately no information is available on whether currently married women are in a polygynous union. Statistical methods The following marital status categories were used in this study: never-married, married or cohabiting 12 months or more (first marriage), widowed less than two years, widowed longer than two years, divorced or separated less than two years, divorced or separated longer than two years, married but widowed in the last two years (MPW), and married but divorced in the last two years (MPD). Those who reported being married could not be separated from those who were simply cohabiting for longer than 12 months as no distinction was made in the questionnaire design. Their experiences may be slightly different because of different social constraints placed upon the relationship; however, the main social construct of interest is stability within a union. In the final regression models, the terms ‘ever-widowed’ and ‘everdivorced’ are used to refer to all those who had ever experienced these events, regardless of their current marital status, given that their experiences are similar. For this reason, those who reported being currently married but had experienced a divorce or spouse’s death in the previous two years were included in either the ‘ever-divorced’ or ‘ever-widowed’ groups as they had experienced a transition from a stable union to its breakdown. Table 1 describes how the different categories of marital status were derived. For the investigation of the relationship between HIV prevalence and marital status, possible explanatory variables relating to the sociodemographic, behavioural and spatial mobility characteristics of participants and their partners were chosen on the basis of findings from earlier studies.
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Spark-du Preez, Zaba, Nyamukapa, Mlilo and Gregson
Table 1: Categorisation of marital status Current marital status Never married Currently married
Widowed
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Divorced or separated
Previous marital status change None None Divorced in last 2 years Widowed in last 2 years None Widowed in last 2 years None Divorced in last 2 years
(n) (1 925) (3 883) (673) (105) (44) (310) (56) (671)
Since sex and age are important confounders in the relationship between marital status and HIV prevalence, firstly bivariate models stratified by sex and controlling for age alone were constructed for each measure in order to identify a subset of variables to consider for subsequent analysis. Logistic regression models were then developed to examine the combined effects of age, marital status and each of the other variables on HIV status. An extensive table of HIV prevalence and age and marital status-adjusted odds ratios for HIV infection among men and women by socio-demographic, behavioural and partner-related variables is available on request. Finally, sex-specific multivariate models were generated to compare the odds of being HIV-positive in each marital status group, after controlling for possible confounders and effect modifiers. Any differences in category coding of variables between males and females reflect observed differentials in HIV prevalence after adjusting for age and marital status. Due to the large number of parameters estimated in the preliminary models, variables that were not significantly associated with the outcome variable (P ≤ 0.05) after controlling for age and marital status were not tested in the multivariate regression models in the interests of parsimony. The order in which variables were removed from the model was determined by their position on the causal pathway (more distant variables were removed first) and the strength of their association with the outcome. The conceptual framework used to determine these relationships is illustrated in Figure 1. Univariate and bivariate data analyses were performed using Stata 7.0 (Stata Co-operation, College Station, Texas, USA) and 95% confidence intervals and P-values were computed for all variables. The Pearson Chi squared test was used to test for differences in HIV prevalence by sociodemographic, sexual behaviour, spatial mobility and partnerrelated characteristics separately for males and females and the significance of each parameter was tested using the Wald statistic. A Receiver Operating Curve (ROC) was used to evaluate the predicted accuracy of the final models. In this case the predicted values generated by the logistic model can be viewed as a continuous indicator to be compared to the observed binary response variable. The area under the curve measures discrimination, i.e. the ability of the test to correctly classify those with and without the outcome. The measure will vary between 0.5 and 1. An area of 0.5 represents the diagonal, attained when no discrimination exists or by chance alone. An area of 1 represents the perfect indicator.
Label Never married Currently married Married previously divorced (MPD) Married previously widowed (MPW) Long-term widow Recently widowed Long-term divorcee Recently divorced
Final category Never married First marriage Ever-divorced Ever-widowed Ever-widowed Ever-widowed Ever-divorced Ever-divorced
Results Univariate and bivariate analyses Sixty per cent of females were currently married or in a cohabiting or long-term relationship (12 months or more) and only 8% were never-married. In contrast, the largest category for males was the never-married group (44%) with 40% being currently married. More female than male respondents were currently divorced/separated (14% vs 5%, respectively) and currently widowed (8% vs 1.1%). These differences partly reflect differences in the age-ranges and distributions between men and women in the study. Similar proportions of men and women who were either divorced or widowed in the two years prior to the study had remarried in this sample (approximately 9% and 1.5% respectively in each case). Whilst the majority of females (59%) married between the ages of 15 and 19, the highest proportion of males (25%) married after age 25. Table 2 presents sex-stratified HIV prevalence by age group and marital status, and age-adjusted odds ratios for HIV infection by marital status. HIV prevalence among male and female study participants who reported having started sexual activity was 22.5% and 30.1%, respectively. HIV prevalence peaks at 46% at ages 30–34 for males and at 40% at ages 25–29 for females. HIV prevalence was highest in the least stable marital status groups. After adjusting for age, being married had a protective effect relative to being never-married for females but the opposite was true for males. Ever-married men and women had similar levels of HIV prevalence but a large sex-differential exists amongst the never-married. For males, the crude odds of being HIVpositive were significantly higher if the individual had been married compared to never having married, whereas for females there was no statistically significant difference between the between the never- and ever-married groups. Roughly 18% of the study group were either currently divorced or separated or had had a divorce in the two years prior to the survey. The equivalent percentage for widowhood was 6%. More women than men reported recent divorce or widowhood. Recent experience of divorce and widowhood were each significantly associated with being HIV-positive (χ2, P < 0.001) for both sexes at all ages as opposed to being never-married, with the exception of the youngest age group (
