Measuring gender and reproductive health in Africa

This article was downloaded by: [University of Missouri Columbia] On: 14 February 2013, At: 08:54 Publisher: Routledge Informa Ltd Registered in England and Wales Registered Number: 1072954 Registered office: Mortimer House, 37-41 Mortimer Street, London W1T 3JH, UK

Culture, Health & Sexuality: An International Journal for Research, Intervention and Care Publication details, including instructions for authors and subscription information: http://www.tandfonline.com/loi/tchs20

Measuring gender and reproductive health in Africa using demographic and health surveys: the need for mixedmethods research Enid Schatz

a b c

& Jill Williams

b c

a

School of Health Professions, University of Missouri, Columbia, USA b

Institute of Behavioral Science, University of Colorado, Boulder, USA c

MRC/Wits Rural Population Health and Health Transition Research Unit (Agincourt), School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa Version of record first published: 16 Jul 2012.

To cite this article: Enid Schatz & Jill Williams (2012): Measuring gender and reproductive health in Africa using demographic and health surveys: the need for mixed-methods research, Culture, Health & Sexuality: An International Journal for Research, Intervention and Care, 14:7, 811-826 To link to this article: http://dx.doi.org/10.1080/13691058.2012.698309

PLEASE SCROLL DOWN FOR ARTICLE Full terms and conditions of use: http://www.tandfonline.com/page/terms-and-conditions 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. The publisher does not give any warranty express or implied or make any representation that the contents will be complete or accurate or up to date. The accuracy of any instructions, formulae, and drug doses should be independently verified with primary sources. The publisher shall not be liable for any loss, actions, claims, proceedings,

Downloaded by [University of Missouri Columbia] at 08:54 14 February 2013

demand, or costs or damages whatsoever or howsoever caused arising directly or indirectly in connection with or arising out of the use of this material.

Culture, Health & Sexuality Vol. 14, No. 7, August 2012, 811–826

Measuring gender and reproductive health in Africa using demographic and health surveys: the need for mixed-methods research


Enid Schatza,b,c* and Jill Williamsb,c a School of Health Professions, University of Missouri, Columbia, USA; bInstitute of Behavioral Science, University of Colorado, Boulder, USA; cMRC/Wits Rural Population Health and Health Transition Research Unit (Agincourt), School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa

(Received 24 January 2012; final version received 25 May 2012) Understanding gender in Africa is essential to creating policy and designing interventions to address key reproductive-health issues such as HIV/AIDS and maternal mortality that are particularly pressing for the continent and are strongly related to gender inequality. The addition of questions to capture women’s empowerment and autonomy on the MEASURE/Demographic and Health Surveys (DHS) in the late1990s expanded opportunities to examine the relationship between gender and reproductive health. These questions provide valuable information on trends and individual-level associations between gender inequality and health. Given that women’s empowerment, status and autonomy are largely dependent on contextuallyspecific gender systems, however, supplementary qualitative studies to validate and contextualise these data would strengthen analyses significantly. This paper provides examples of how such mixed-methods work would improve understandings of gender and reproductive health in Africa by validating survey questions, providing insights into how to analyse and interpret DHS data and illuminating the processes and mechanisms behind gendered experiences. Additionally, this work could help improve future survey research on gender and reproductive health. Keywords: Africa; DHS; qualitative methods; mixed-methods; gender

Introduction Africa is facing many well documented demographic and health challenges. The continent consistently reports the highest rate of population growth in the world and faces significant reproductive health issues including high maternal mortality, endemic HIV/AIDS and high levels of sexually transmitted infections (Bloom 2011; Ronsmans and Graham 2006; UNAIDS 2010; WHO 2001). Because many African countries lack health systems that record demographic and health events, large representative surveys such as the MEASURE/Demographic and Health Surveys (DHS) are important tools for documenting reproductive and sexual health issues. DHS data are publically available and widely used and have, therefore, contributed significantly to increasing reproductive health knowledge in Africa. Research has shown that gender inequality is among the primary drivers for the pressing African reproductive health problems noted above (Ronsmans and Graham 2006; Smith 2002). However, the quantitative study of gender inequality and its impact on health

*Corresponding author. Email: [email protected] ISSN 1369-1058 print/ISSN 1464-5351 online q 2012 Taylor & Francis http://dx.doi.org/10.1080/13691058.2012.698309 http://www.tandfonline.com


812

E. Schatz and J. Williams

in sub-Saharan Africa is limited (Dodoo and Frost 2008; Schatz 2003; Williams 2010). This limit has historically been due to a lack of interest in gender in the field of demography and the resulting lack of data on gender (Williams 2010). Much of the work connecting gender to health in Africa has been qualitative and related to HIV/AIDS (e.g. Cummings et al. 2006; Mantell et al. 2009). The DHS in the last decade, however, expanded to include questions assessing a few dimensions of gender inequality – decision-making, access to health care and attitudes about control over sex and men’s use of violence (see Appendix). Demographic and health survey data from more than 30 sub-Saharan African countries provide a starting point from which to assess the impact of gender on health at the macro level. The literature on which the DHS questions were based, however, was focused on Asian cultures where demographic research first showed that women’s education and autonomy impacted fertility and reproductive health (Hashemi and Schuler 1993; Mason 1986). In many Asian settings, women’s autonomy is restricted by cultural practices such as purdah (the seclusion of women), therefore the questions might not translate to African contexts. In fact, comparative research using DHS data has clearly demonstrated that women’s empowerment, status and autonomy are largely dependent on contextually-specific gender systems (Desai and Johnson 2005; Kishor 2005; Kishor and Neitzel 1996; Kishor and Subaiya 2008). For these reasons we raise two related questions. First, how can we improve the use of existing DHS data for understanding the relationship of gender to pressing African reproductive health issues? And, second, how could future DHS data on gender be improved? In brief, the answer to each question involves the need for mixed-methods research on gender and health utilising DHS data. To better exploit existing DHS data on gender, scholars need to supplement DHS data from sub-Saharan Africa with qualitative studies to contextualise and validate existing measures and the resulting research should be used to inform and alter future DHS surveys. While population scientists historically have relied primarily on surveys and censuses, there has been a recent shift toward mixed-methods research, which can contextualise and validate quantitative analyses on complex topics like gender, reproductive health and AIDS (Axinn and Pearce 2007; Schatz 2012). In mixed-methods research, the strengths of one method can make up for the weaknesses of another (Knodel 1997; Obermeyer 1997; Pearce 2002; Randall and Koppenhaver 2004). Articles reporting mixed-methods research are increasingly seen in major population studies journals (e.g. Mojola 2011; Stewart et al. 2008; Watkins 2004). Furthermore, African demographic and public health training programmes are increasingly promoting qualitative and mixed-methods research for doctoral students.1 Qualitative studies of gender and health from sub-Saharan Africa are abundant. However, very few studies have matched qualitative data with DHS data to enhance DHS analyses (exceptions: Agadjanian 2002; Mojola 2011). After providing a brief history of the development of the DHS questions on gender, we present ways that DHS data could be used in mixed-methods designs. We outline how this mixed-methods approach will help build a more complex understanding of gender and context, examine the validity of survey questions and elucidate the processes and mechanisms behind gendered experiences at the individual and community level. Finally, we offer some practical suggestions for supplementing DHS data with small qualitative projects, provide recommendations on how this work might inform future DHS data collection and discuss limitations of mixing qualitative methods with existing DHS data from sub-Saharan Africa.


Culture, Health & Sexuality

813

Reforming DHS measures of gender For the past 25 years, Measure DHS has provided technical assistance to governmental partners in developing countries to implement nationally (or regionally) representative household surveys (www.measuredhs.com). Over 200 DHS surveys in 75 countries have been completed. With samples ranging from 5000 to 30,000 households, surveys generally are repeated every five years, providing longitudinal data to assess trends in fertility, family planning, maternal and child health, as well as child survival, HIV/AIDS, malaria and nutrition. Funded primarily by USAID, these surveys provide standardised measures, making comparative analyses possible. Originally, the DHS only included proxy measures of women’s status such as age at marriage, education and employment. After consulting a panel of experts on gender in 1997, the DHS introduced direct gender measures in 1999 (Kishor 2005). These measures were embedded in a theoretical framework that defines gender as socially constructed and connects gender inequality to important population, health and nutrition outcomes (Kishor 2005). Standard DHS surveys measure gender inequality through women’s participation in household decisions and women’s attitudes about wife beating and situations when a woman can refuse to have sex with her husband, as well as obstacles women face in obtaining healthcare (see Appendix). As with the rest of the questions in the DHS, questions about gender are designed to be standard across settings. In addition to adding gender to the core women’s questionnaire, DHS created new standardised modules, which run alongside the core questionnaires, to gather more detailed information on particular aspects of women’s lives. Modules are available to measure domestic violence, female genital cutting (FGC), maternal mortality and fistula.2 The DHS has conducted standard and/or special surveys in over 30 sub-Saharan African countries in the last decade, but only a limited number of countries have completed the special modules. Therefore, this paper focuses more generally on how qualitative data might supplement the gender questions on the core questionnaire of the standard survey. In sub-Saharan Africa, in particular, an important weakness of the DHS variables is the over-emphasis on measures more appropriate for Asian cultural contexts than for Africa.3 For example, in many Asian contexts purdah, the practice of keeping women separate from men, limits women’s freedom of movement in public spaces, whereas limited mobility is less of an issue in most African contexts (Nyanzi et al. 2005; Schatz 2003, 2012). Although DHS Surveys have included questions about women’s work that are more relevant to many African contexts, more information about women’s power in the public, rather than the private, sphere would be important for understanding and identifying variation in the power of women. Interestingly, DHS has completed a number of qualitative projects in sub-Saharan Africa related to gender. While not explicitly focused on women’s status and empowerment, DHS has used qualitative projects to shed light on sensitive topics. The topics range from how young women cope with an unexpected pregnancy (open-ended interviews in Accra, Ghana), to how to produce better survey questions and pre-coded responses to questions on FGC (semi-structured interviews and focus group discussions in Guinea) (Yoder, Camara, and Soumaoro 1999), to how to adjust questions that respondents did not understand in the way intended for an AIDS indicator study (observational study of survey implementation in Tanzania). To our knowledge, however, these data have not been used to alter questions on core questionnaires or modules related to women’s status, empowerment or autonomy. Since 1999, analysis of DHS data has helped demonstrate the contextually-specific nature of gender and has shown that relationships between gender inequality and health

814


outcomes are varied and contextually-specific (Kishor 2005; Kishor and Neitzel 1996; Kishor and Subaiya 2008). Meanwhile, qualitative research has illuminated the processes and mechanisms by which gender inequality influences health and has suggested new dimensions of women’s and men’s power related to reproductive health (Cummings et al. 2006; Pettifor et al. 2012; Schatz 2003). Researchers have often used mixed-methods designs to improve knowledge about gender and health or to improve survey research (Mitchell et al. 2007; Schatz 2003). However, rarely is this mixed-methods design used with DHS surveys (Agadjanian [2002] and Mojola [2011] are important exceptions).


Gaining from mixed-methods research designs Despite the overall validity and reliability of large scale surveys, ‘the strength of comparative surveys . . . is also their weakness: Precisely because they are, at least in principle, collected in exactly the same way in all settings, the data they yield are limited when the goal of the research is to provide explanations for observed associations, differences between groups, or trends over time.’ (Obermeyer 2005, 3)

Given the limitations outlined above, qualitative research is a vital tool for understanding the ways gender is enacted in the survey setting, for identifying concepts and for differentiating between dimensions of women’s status, empowerment and autonomy. Qualitative data can then be used to guide analyses of existing DHS data. Ideally, the methodological process is iterative, with a qualitative component as a starting-, mid- and end-point. In such a scenario, qualitative data would be used to develop and validate survey questions. Then further qualitative data collection in conjunction with the survey would increase the researchers’ understanding of gender in the context and frame quantitative models. Finally, post-survey qualitative data collection would help interpret quantitative findings. Although the iterative process is not possible for independent researchers using DHS secondary data, mixed-methods research designs can accomplish many of the same goals and even small qualitative projects using fairly quick evaluation methods can greatly improve the understanding of gendered processes and the interpretation of quantitative measures or findings. Small qualitative projects can be used to corroborate, elaborate and initiate new ways of understanding DHS data (Rossman and Wilson 1985). Collecting and analysing qualitative data can help ensure that quantitative models appropriately represent gendered dynamics and women’s status, empowerment and autonomy in the given setting. And because DHS data are free to researchers, the monetary and time costs of mixed-methods designs with the DHS are reasonable. A number of authors call for the use of mixed-methods research to better understand topics in which gendered relations are a central issue, for example reproductive health, sexual behaviour and HIV/AIDS, and development (Bamberger 2000; Helitzer-Allen, Makhambera, and Wangel 1994; Obermeyer 2005). The DHS website notes that ‘qualitative and quantitative approaches to the study of social interaction can complement one another. This strategy focuses on local terms, concepts and practices to achieve understanding, and explores the social and cultural contexts within which events occur’ (http://www.measuredhs.com/What-We-Do/Survey-Types/Qualitative-Research.cfm). Thus, qualitative work could be included for at least one point in time (beginning, mid-point or end) to supplement quantitative analyses of the DHS, providing this focus on local terms, concepts and practices to elicit an understanding of gender in a particular cultural context. Qualitative methods are better than surveys at ‘elicit[ing] sensitive information on determinants of behavior [sic] such as attitudes and social norms, as well as the cultural context in which these behaviors [sic] take place’ (Helitzer-Allen, Makhambera,


815

and Wangel 1994, 75). In addition, qualitative data can get at the meaning of behaviours and attitudes related to gender and both why and how they change over time (Obermeyer 2005). Local meanings and their relationship to broader social structures can be captured more fully through open-ended discussions than with fixed-answer questions. Even when survey data point to correlations between two sets of variables, like those between women’s status, empowerment, and autonomy and reproductive health outcomes, the processes and mechanisms involved remain hidden.4 Qualitative analyses shed light on these pathways, even after the survey data has been collected and analysed.


Supplementing DHS data with qualitative data collection A small number of studies have successfully incorporated DHS data into mixed-methods designs (e.g. Agadjanian 2002; Mojola 2011). They show how the DHS can elicit important questions best examined further through qualitative research. The sections below outline examples of how qualitative methods can be and have been used to improve analyses of DHS data on gender and reproductive health in Africa. We highlight how supplemental qualitative data can: (1) help understand the meaning of DHS variables and guide variable choice for quantitative models, (2) contextualise quantitative findings and identify the mechanisms through which gender inequalities affect health, and (3) explore community-level influences and gendered norms and their relationship to individuals’ reproductive health outcomes. Getting the meaning right While DHS questions are standardised across settings, are these questions heard and answered in standard ways? In order for measures to be valid, respondents must understand the content of the question, remember accurately, give answers that correctly reflect their memory and want to provide truthful answers (Obermeyer 2005). A key to advancing quantitative DHS analyses of gender in sub-Saharan Africa is making use of qualitative data to improve variable choice and determine which questions are most likely to be related to the outcome of interest. Focus group discussions (FGDs) or individual interviews could improve the validity of quantitative analyses by improving the understanding of the questions that go into analytical models. Understanding what the questions are actually measuring is essential for selecting variables and for building any related indices. The decision-making questions in the DHS provide a good example of where this type of understanding is needed. These questions attempt to reveal the distribution of power within households by quantifying the weight given to a wife’s desires versus those of her husband in making a decision such as what to cook or purchase or whether or not to go to the doctor. Some research using DHS data has suggested that women may actually be better off in situations where they make fewer decisions independently of their partners. Using DHS data for Zambia and Malawi, Hindin (2005) finds that women who have the ‘final say’ or whose partners do not have the ‘final say’ are more likely to have chronic energy deficiency than would be expected. Hindin suggests that more needs to be understood about these situations: are these women empowered to make decisions or do they represent households where partners contribute little and women are left to take care of themselves and their children? Does the decision reflect true empowerment or economic desperation, which forces women to act on their own? In order to better understand the way these questions are understood by respondents and what their responses mean, either FGDs or individual interviews could ask which


816


decisions women are included in and in what ways, whether women want to be a part of larger decisions and why or why not. In FGDs, women and men could discuss or come to a consensus about how to order the responses (wife decides, husband decides, decide jointly) in terms of women’s power in decision-making. In individual interviews, a sample of individuals similar to DHS respondents in age, marital status, education level and other variables could be asked the questions under review. Rather than moving from one precoded question to the next, however, the interviewer could engage with the respondent in a cognitive interview (Willis 2005) – a semi-structured conversation following each question, to understand how the respondent heard the question, her interpretation of its meaning and what she was thinking about (a particular situation or occurrence, or many experiences) when she selected her response to the question (Schatz 2003, 2012). As in the FGDs, more detailed questions could be asked about a woman’s influence in decisions in the household and relative power when making decisions alone or jointly with her partner. Such detailed qualitative research may be the only way to understand what women feel is the most empowering scenario regarding various decision-making situations. Re-asking these questions and allowing respondents to give examples in an open-ended discussion may clarify the ways in which the questions were understood and answered on the survey. This alerts the researcher and future analyst when a particular survey response might be associated with a greater or lesser sense of status, empowerment or autonomy. In this way, small qualitative projects can help researchers understand what questions are measuring, which questions to use in their models and how best to operationalize the available data. Exploring the context, processes and mechanisms of gender inequalities Obermeyer (2005) notes that qualitative research can ‘document the ways in which information about health is filtered through local structures and incorporated into existing systems of understanding, especially in the case of HIV’ (7). One way of contextualising DHS data analysis is to broaden literature reviews to include qualitative work across disciplines (Obermeyer 1997; Randall and Koppenhaver 2004). In addition, qualitative studies are important for understanding the process of gender – how gender inequalities emerge and influence behaviour related to demographic and health outcomes in particular contexts. Focus group discussions can afford insights into local values and norms related to gender (Castle et al. 1999; Mantell et al. 2009). Individual interviews can uncover ways that gender affects women’s and men’s experiences in their daily lives (Cummings et al. 2006; Pettifor et al. 2012). For example, Castle and colleagues’ (1999) study of clandestine contraceptive use in Mali highlights ways in which qualitative research on gender and context provides important (and sometimes counterintuitive) information for reproductive health policy and programmes. Qualitative evidence from their FGDs and individual interviews shows that bringing men into family planning programming and redirecting programmes toward ‘couple-oriented counseling’ may be wrong-headed and may harm women in settings where contraceptive uptake is still low. In such settings, men may still be resistant to contraceptive use, so that women who use contraception covertly are at risk of being found out and left in a hostile environment if men are brought into the process. Without knowledge of how gender is enacted in this context, it would be difficult to analyse the relationship between women’s autonomy in making decisions about contraception with their reproductive health behavior. Agadjanian (2002) provides another excellent example for how DHS data and qualitative research can be synergistic and improve our knowledge of gendered processes



817

and how they affect reproductive health. Using the 1997 DHS survey in Mozambique, Agadjanian found that despite men’s and women’s knowledge about modern contraception, uptake was low. Furthermore, DHS data revealed that both men and women were much more likely to discuss family planning with friends and neighbours than with spouses or relatives. Agadjanian conducted FGDs and in-depth interviews with men in Mozambique and included questions about their communication about contraception with friends. This supplemental data showed that men’s separate social networks lead to highly gendered informal communication loops that ‘feeds back into gender ideology by reaffirming and challenging gender hierarchies, roles and stereotypes’ (195). The qualitative work highlights that men’s informal networks are an important and gendered source of information about family planning. Many of their conversations about contraceptive use take place in age-sex-class segregated networks and significantly impact men’s attitudes about reproduction and contraceptive preferences. While quantitative analysis revealed low contraceptive use and communication about family planning with spouses, qualitative research revealed how men’s peer communication networks influence their attitudes and preferences regarding family planning. Scaling up: beyond individual measures of gender Much of the literature on gender has shown that women’s empowerment at the community level often has more explanatory power than do individual characteristics (Desai and Johnson 2005; Mason 1987; Mason and Smith 2000; Matthews et al. 2005). The DHS surveys provide individual level data. Qualitative data that provide a general understanding of how gender is lived in a particular context could illuminate community norms and attitudes, as well as suggest the appropriate level of aggregation of individuallevel data for quantitative analyses. Scaling up from the individual to the community level can be accomplished by collecting data on institutional influences on gender or by using qualitative methods to gather information about the ways macro-contextual variables influence micro-level behaviour. One way in which participant observation could elucidate the setting’s gendered context is through simply recording information about the setting’s geographical layout. Schatz’s (2003) study from Malawi provides an example of how even this basic information can be crucial to understanding survey data on women’s status, empowerment and autonomy. In the Malawi Diffusion and Ideational Change Project (MDICP), differences between the southern and northern study sites greatly determined the distributions of freedom of movement variables from the 1998 MDICP survey. In the northern, patrilineal site, women reported having more freedom of movement than in the southern, predominantly matrilineal area. Participant observation as part of a larger qualitative study revealed that the main reason was that in the northern site the market and health centre were embedded within the community, but in the southern site they were located on a major road near a large trading centre. It was the ‘dangers’ posed by the main road and trading centre that constrained women’s mobility in the southern site. Such geographic barriers to women’s access to health care might require different policy responses than if the barriers were related to knowledge or even empowerment. Focus group discussions are particularly useful for assessing women’s empowerment at a community level because they can capture both consensus and dissent about particular topics during group discussions. Varga’s (2003) article highlights the advantages of mixed-methods research, particularly for gender and reproductive health topics, and especially the advantages of conducting FGDs as an initial strategy. Varga used a total of

818



24 FGDs, stratified by sex, age and urban/rural residence, to define ‘social parameters of adolescent sexuality and fertility dynamics by gauging relevant attitudes about contraceptive use, and pregnancy; by assessing sensitivity about these issues; and by gaining a better understanding of potentially relevant linguistic and sub-cultural differences between rural and township adolescents’ (162). The FGDs uncovered gendered consequences of paternity denials. The denial of paternity damages a girl’s, but not a boy’s, respectability. Denial of paternity is viewed as normative, particularly in urban areas, and can increase a young man’s status among his peers. It is through the understanding of these gendered norms at the community level that behavior related to gender and reproductive outcomes captured in the DHS become clearer. Advancing research on gender using mixed-methods designs with DHS data Information on the meaning of questions, processes and mechanisms, as well as gender systems and context, is more richly captured through qualitative methods, rather than fixed-choice survey questions. While the above examples range in size and scope of qualitative projects, the underlying message is that a little knowledge about how questions are understood, geography, gendered power relationships and community norms and values can go a long way in providing context as well as a basis on which to make decisions about variable selection for DHS analysis and interpretation of statistical results. Validating, contextualising and scaling-up DHS data on gender are important goals for adding qualitative research to DHS analysis. Furthermore, mixed-methods projects can advance the broader research agenda on gender in Africa. Significant qualitative work has already begun adding men’s voices to studies of how gender influences couples’ negotiations about sex, contraception and paternity (e.g. Agadjanian 2002; Varga 2003; Wolff, Blanc, and Ssekamatte-Ssebuliba 2000). However, more work is needed since gender measures until recently were largely collected through women’s responses in DHS and other surveys (Dodoo and Frost 2008). The most recent version of the men’s DHS core questionnaire includes certain questions about how men view women’s empowerment and autonomy. Combining survey results with FGDs with both men and women can provide insight into how men’s and women’s responses to similar survey questions are based on similar or different ways of viewing the same situation. Mixed-methods work can also enrich macro analysis. Trend data have shown the extent of reproductive health issues in Africa. Without a sense of the processes and mechanisms that drive trends and underlie cross-national differences, however, it is difficult to develop programmes to improve women’s lives and address reproductive health needs. Qualitative data can provide the meaning behind patterns that emerge from the quantitative data. Like Agadjanian (2002), Wolff and colleagues (2000) use qualitative data to ‘shed light on the variable and often one-sided nature of “discussion” [of sexual issues] reported in surveys’ (128). They find that ‘discussions’ about family planning can have social costs because of perceived associations with infidelity and with having children outside of a union. In their study of marriage and contraceptive use in Tanzania, Hollos and Larsen (2004) claim that ‘an ethnographically informed understanding is essential for the appreciation of culturespecific variables that account for the dynamics of particular marital unions’ (274). The same claims could be made for other issues related to gender and women’s status, empowerment and autonomy. As this paper and their paper argue, ‘the combination of qualitative and quantitative methods should help move the field’ (274) by generating a better understanding of how gender systems function in a particular context and building conceptually-grounded quantitative analyses based on qualitative findings.



819

Drawbacks and challenges of doing qualitative supplemental research for DHS Demography as a discipline has, on the whole, adopted non-anthropological qualitative methods, which rely heavily on FGDs and in-depth interviews and less on participant observation and emersion in the culture. These are generally smaller-scale projects, which are less time and resource intensive. They may also be less effective in understanding cultural context. However, our argument is that using smaller scale qualitative research in conjunction with DHS survey analysis will produce better knowledge than survey analysis alone, particularly in relation to gender. The time and energy spent on qualitative fieldwork that builds on a public-access dataset like the DHS could have synergistic effects, enriching knowledge of a place and deepening the conceptualisation of DHS analyses. Even so, there are a number of challenges to doing supplemental qualitative work in Africa, including accounting for possible bias, determining the scope of the project and training. Addressing sampling bias Qualitative research, like quantitative research, is at risk of various types of bias. In qualitative studies, non-probability sampling is common and can be rife with selection bias. Fox and colleagues (2007) use qualitative data to provide an intimate picture of gender power relations and the ways violence and abuse influence (1) women’s experiences with partners and spouses, (2) women’s economic dependence, and (3) the relationship of both to risk of HIV. Their work provides important insights about gender in South Africa, but, as the authors point out, caution is needed in generalising their results to all women, or even women who have suffered other types of abuse. Their sample was made up of self-selected women who were seeking support against domestic violence and these women were likely very different from women that experience domestic violence but do not seek support. The selectivity of the sample likely had a significant impact on the study findings. Thus, it is important to be aware of how the respondents’ interests may shape their willingness to participate in a study as well as ways they answer the questions (Miller, Zulu, and Watkins 2001). On the other hand, it is also important for researchers not to assume that random samples are the best way to collect supplemental qualitative data (Small 2009). By randomly selecting respondents, researchers might miss including important constituents who have more pertinent knowledge about the variables of interest than those found through a random sample. Selecting appropriate sites or sub-populations for qualitative supplements, especially in such large and diverse countries as those in Africa, is likely to be difficult and could introduce bias. Still, even purposefully selected sub-populations and small single site projects are likely to add to a researcher’s understanding of gender and reproductive health in the general context and aid in DHS analysis. When using qualitative research in mixed-method designs with DHS data, it is important to analyse the potential bias from each data source in order to determine the best qualitative sampling design. Determining the scope of qualitative research projects Developing and conducting a qualitative project involves intensive financial, time and energy commitments to enter the community, establish rapport, select informants, interview them and transcribe and analyse the interviews. Researchers new to qualitative methods must be aware of the magnitude of effort needed and be careful not to attempt too much. The resources needed for a qualitative project are determined by the scope of the project. Qualitative research that might supplement DHS data could range from a small


820


project conducted by a master’s or doctoral student to complement quantitative thesis analyses, to much larger, even multi-sited, projects by an established researcher. In the former case, perhaps 5 to 10 FGDs or 20 to 60 individual interviews could be conducted in one site to achieve sufficient variation, with a few weeks spent in the site observing and taking notes on the context, geography and gender interactions. In the latter case, a multisited, multi-method project involving larger numbers of FGDs and/or individual interviews might be more appropriate. It is likely that none of these projects would be representative of the entire country. It is possible, however, that small purposeful samples in select locales can provide insight into the most fruitful ways to analyse DHS survey questions related to gender and reproductive health. Qualitative projects should not simply be added to produce anecdotal examples or quotes. There are two prongs of knowledge needed for such projects: (1) knowledge about social norms and cultural scripts around gender, so as to not offend participants or strain community relationships, and (2) understand the particulars of community entry and training interviewers, as well as rigorously conduct sampling, data collection and analysis for such projects. For the latter, many good texts are available to use as guides (Bryman 2006; Esterberg 2001; Tashakkori and Teddlie 2003; Teddlie 2009). Qualitative research training in Africa The number of African demographic and health professionals remains limited and this may lead to concern related to qualitative research capacity. In recent years, however, there have been large scale investments to help build advanced regional training programmes in Africa (e.g. Williams et al. 2010). These training programs are increasingly interdisciplinary and increasingly emphasize the importance of qualitative and mixed-methods research. There is, therefore, a growing pool of scholars willing and able to undertake qualitative work that can supplement their analysis of DHS data. While some might argue that only highly trained researchers with impeccable command of local languages can produce rigorous qualitative studies, it has also been our experience over 15 years of doing research projects in Africa that, with proper supervision, local interviewers can be trained and can do high quality qualitative projects (for examples of studies conducted by local interviewers in Africa see Angotti 2012; Madhavan, Townsend, and Garey 2008; Schatz 2003; Schatz and Ogunmefun 2007; Watkins 2004). Conclusion Supplementing DHS data with qualitative work is a way to exploit the benefits of mixedmethods designs and improve our knowledge about gender and important reproductive and sexual health issues in Africa. While DHS data can reveal what components of gender inequality are related to reproductive and sexual health, qualitative projects can reveal how gender inequality operates in local contexts. The combination of quantitative and qualitative results can improve our ability to redress gender and health inequities through local policy and healthcare delivery reform. Mixed-method designs are also an important mechanism for assessing the appropriateness of current DHS measures of gender in the African context. In the decade-plus since the gender questions were developed our understanding of gender has grown. The DHS website designates the current core questionnaire, ‘Phase 6’, to be used from 2008 to 2013 (http://measuredhs.com/What-We-Do/Survey-Types/DHS-Questionnai res.cfm). This highlights the timeliness of revisions, which a regionally diverse panel of



821

experts could conduct by reviewing existing data or commissioning new research to assess the gender questions. Ideally such a process would make use of a number of mixedmethods approaches, including data-linked nested studies re-interviewing DHS survey respondents soon after the survey to validate and adjust questions. In such a design, a small sub-sample of DHS respondents, perhaps particularly interesting or anomalous cases, would be followed-up with a more intensive investigation (Pearce 2002; Schatz 2012). We believe it is time to acknowledge the cultural specificity of the relationship between gender inequality and reproductive health demonstrated by both qualitative and quantitative research. In revising future surveys, it seems appropriate to sacrifice uniformity and comparability for specificity in order to better inform health policy. Rather than trying to generalise about what gender is, it would be more productive to have DHS and other surveys structured to generalise about how gender works. While gender inequality may be universal, we need to move toward understanding the context-specific mechanisms through which gender inequality affects health. Mixed-methods approaches – using qualitative data to inform DHS survey questions, existing data and analytical work – will allow researchers to further develop ways to capture, measure and compare gender across settings and over time, ultimately improving our understanding of common and unique relationships of gender to reproductive health in Africa and providing insights as to how to address needs and improve lives through policy and programs. Acknowledgements We thank Paulina Adebusoye, Akosua Adomako Ampofo, Nicole Angotti, Monica Grant, Sanyu Mojola, Tola Pearce, Rachel Snow and four anonymous reviewers for comments on previous drafts. Earlier versions of this paper were presented at the IUSSP International Seminar on Gender and Empowerment in theTwenty-First Century in Africa, in Nairobi, Kenya (July 2009) and at the 2011 Population Association of America Annual Meeting.

Notes 1. The authors have worked extensively for 10 years with several training programmes, students and researchers in South Africa, Kenya and Ghana. 2. Prior to 2012, there was an available module entitled Women’s Status and Empowerment. Countries that have implemented one of these ‘extra’ modules requested its inclusion as part of survey implementation. 3. While there is no public record of the advisory committee that developed these questions, according to Sunita Kishor (personal communication, 2009) who was on the committee, the members were largely experts on Asia, with very few research experts on Africa. 4. See Figure 1 in Kishor (2005) for a conceptual outline of the relationships among sex, gender and Population/Health/Nutrition variables, which include reproductive health measures.

References Agadjanian, Victor. 2002. Men’s talk about ‘women’s matters’: Gender, communication and contraception in urban Mozambique. Gender & Society 16, no. 2: 194– 215. Angotti, Nicole. 2012. Testing differences: The implementation of Western HIV-testing norms in sub-Saharan Africa. Culture, Health & Sexuality 14, no. 4: 365– 78. Axinn, William, and Lisa Pearce. 2007. Mixed methods data collection strategies. Cambridge: Cambridge University Press. Bamberger, Michael. 2000. Integrating quantitative and qualitative research in development projects. Washington, DC: World Bank. Bloom, David E. 2011. Seven billion and counting. Science 333, no. 6042: 562– 9. Bryman, Alan. 2006. Integrating quantitative and qualitative research: How is it done. Qualitative Research 6, no. 1: 97 – 113.


822


Castle, Sarah, Mamadou Kani Konate, Priscilla R. Ulin, and Sarah Martin. 1999. A qualitative study of clandestine contraceptive use in urban Mali. Studies in Family Planning 30, no. 3: 231–428. Cummings, Beverley, Meseret Mengistu, Wubalem Negash, Abeba Bekele, and Tadesse Ghile. 2006. Barriers to and facilitators for female participation in an HIV-prevention project in rural Ethiopia: Findings from a qualitative evaluation. Culture, Health & Sexuality 8, no. 3: 251–66. Desai, Sonalde, and Kiersten Johnson. 2005. Women’s decisionmaking and child health: familial and social hierarchies: A focus on gender. Collected Papers on Gender Using DHS Data. Measure/DHS. http://www.measuredhs.com/publications/publication-OD32-Other-Documents.cfm Dodoo, F. Nii-Amoo, and Ashley E. Frost. 2008. Gender in African population research: The fertility/reproductive health example. Annual Review of Sociology 34, no. 1: 431– 52. Esterberg, Kristin G. 2001. Qualitative methods in social research. 1st ed. Boston, MA: McGrawHill Humanities/Social Sciences/Languages. Fox, Ashley M., Sharon Jackson, Nolwazi Gasa, Mary Crewe, and Kathleen Sikkema. 2007. In their own voices: A qualitative study of women’s risk for intimate partner violence and HIV in South Africa. Violence Against Women 13: 583– 602. Hashemi, Syed M., and Sidney Ruth Schuler. 1993. Defining and studying empowerment of women: A research note from Bangladesh. JSI Working Paper No. 3. Arlington VA: JSI. Helitzer-Allen, Deborah, Mercy Makhambera, and Anne-Marie Wangel. 1994. Obtaining sensitive information: The need for more than focus groups. Reproductive Health Matters 2, no. 3: 75 – 82. Hindin, Michelle. 2005. Women’s autonomy, status and nutrition in Zimbabwe, Zambia and Malawi. In A focus on gender: Collected papers on gender using DHS data, ed. Sunita Kishor. Measure/DHS. http://www.measuredhs.com/publications/publication-OD32-Other-Documents. cfm Hollos, Marida, and Ulla Larsen. 2004. Marriage and contraception among the Pare of northern Tanzania. Journal of Biosocial Science 36: 255– 78. Kishor, Sunita. 2005. Introduction. A focus on gender: Collected papers on gender using DHS data. Measure/DHS. http://www.measuredhs.com/publications/publication-OD32-Other-Documents. cfm Kishor, Sunita, and Katherine Neitzel. 1996. Status of women: indicators for twenty-five countries. DHS Comparative Reports. Calverton, MD: MacroInternational. http://www.measuredhs.com/ publications/publication-CS21-Comparative-Reports.cfm Kishor, Sunita, and Lekha Subaiya. 2008. Understanding women’s empowerment: a comparative analysis of Demographic and Health Surveys (DHS) data. DHS Comparative Reports. Calverton, MD: MacroInternational. http://www.measuredhs.com/publications/publicati on-CR20-Comparative-Reports.cfm Knodel, John. 1997. A case for non-anthropological qualitative methods for demographers. Population and Development Review 23, no. 4: 847– 53. Madhavan, Sangeetha, Nicholas Townsend, and Anita Garey. 2008. ‘Absent breadwinners’: Fatherchild connections and paternal support in rural South Africa. Journal of Southern African Studies 34, no. 3: 647– 63. Mantell, Joanne, Sarah Needham, Jennifer Ann Smit, Susie Hoffman, Queen Cebekhulu, Jessica Adams-Skinner, Theresa Exner, et al., 2009. Gender Norms in South Africa: Implications for HIV and pregnancy prevention among African and Indian women students at a South African tertiary institution. Culture, Health & Sexuality 11, no. 2: 139– 57. Mason, Karen Oppenheim. 1986. The status of women: Conceptual and methodological issues in demographic studies. Sociological Forum 1, no. 2: 284– 300. Mason, Karen Oppenheim. 1987. The impact of women’s social position on fertility in developing countries. Sociological Forum 2, no. 4: 718– 45. Mason, Karen Oppenheim, and Herbert L. Smith. 2000. Husbands’ versus wives’ fertility goals and use of contraception: The influence of gender context in five Asian countries. Demography 37, no. 3: 299– 311. Matthews, Zoe, Martyn Brookes, R. William Stones, and Mian Bazle Hossain. 2005. Village in the city: Autonomy and maternal health-seeking among slum populations of Mumbai. A focus on gender: Collected papers on gender using DHS data. Measure/DHS. http://www.measuredhs. com/publications/publication-OD32-Other-Documents.cfm Miller, Kate, Eliya Msiyaphazi Zulu, and Susan Cotts Watkins. 2001. Husband-wife survey responses in Malawi. Studies in Family Planning 32, no. 2: 161– 74.



823

Mitchell, Kirstin, Kaye Wellings, Gillian Elam, Bob Erens, Kevin Fenton, and Anne Johnson. 2007. How can we facilitate reliable reporting in surveys of sexual behaviour? Evidence from qualitative research. Culture, Health & Sexuality 9, no. 5: 519– 351. Mojola, Sanyu A. 2011. Multiple transitions and HIV risk among orphaned Kenyan schoolgirls. Studies in Family Planning 42, no. 1: 29 –40. Nyanzi, Barbara, Stella Nyanzi, Brent Wolff, and James Whitworth. 2005. Money, men and markets: Economic and sexual empowerment of market women in southwestern Uganda. Culture, Health & Sexuality 7, no. 1: 13 – 26. Obermeyer, Carla Makhlouf. 1997. Qualitative methods: A key to a better understanding of demographic behavior? Population and Development Review 23, no. 4: 813– 8. Obermeyer, Carla Makhlouf. 2005. Reframing research on sexual behavior and HIV. Studies in Family Planning 36, no. 1: 1 – 12. Pearce, Lisa D. 2002. Integrating survey and ethnographic methods for systematic anomalous case analysis. Sociological Methodology 32: 103– 32. Pettifor, Audrey, Catherine MacPhail, Althea D. Anderson, and Suzanne Maman. 2012. ‘If I buy the Kellogg’s then he should [buy] the milk’: Young women’s perspectives on relationship dynamics, gender power and HIV risk in Johannesburg, South Africa. Culture, Health & Sexuality 14, no. 5: 477– 90. Randall, Sara, and Todd Koppenhaver. 2004. Qualitative data in demography: The sound of silence and other problems. Demographic Research 11: 57 – 96. Ronsmans, Carine, and Wendy J. Graham. 2006. Maternal mortality: Who, when, where and why. Lancet 368: 1189– 200. Rossman, Gretchen B., and Bruce L. Wilson. 1985. Numbers and words: Combining quantitative and qualitative methods in a single large-scale evaluation study. Evaluation Research 9, no. 5: 627– 43. Schatz, Enid. 2003. Comparing, contextualizing, and conceptualizing: Enhancing quantitative data on women’s situation in rural Africa. Demographic Research Suppl. 1, no. 5: 143– 74. Schatz, Enid. 2012. Rationale and procedures for nesting semi-structured interviews in surveys or censuses. Population Studies 66, no. 2: 183– 195. Schatz, Enid, and Catherine Ogunmefun. 2007. Caring and contributing: The role of older women in multi-generational households in the HIV/AIDS era. World Development 35, no. 8: 1390 –1403. Small, Mario Luis. 2009. ‘How many cases do I need?’ Ethnography 10, no. 1: 5 – 38. Smith, Mohga Kamal. 2002. Gender, poverty, and intergenerational vulnerability to HIV/AIDS. Gender & Development 10, no. 3: 63 – 70. Stewart, Miriam, Edward Makwarimba, Alison Barnfather, Nicole Letourneau, and Anne Neufeld. 2008. Researching reducing health disparities: Mixed-methods approaches. Social Science & Medicine 66, no. 6: 1406– 1417. Tashakkori, Abbas, and Charles Teddlie. 2003. Handbook of mixed methods in social and behavioral research. Thousand Oaks, CA: Sage. Teddlie, Charles. 2009. Foundations of mixed methods research: Integrating quantitative and qualitative approaches in the social and behavioral sciences. Thousand Oaks, CA: Sage. UNAIDS. 2010. Global report: UNAIDS report on the global AIDS epidemic. Joint United Nations Programme on HIV/AIDS. http://www.unaids.org/globalreport/documents/20101123_Global Report_full_en.pdf Varga, Christine A. 2003. How gender roles influence sexual and reproductive health among South African adolescents. Studies in Family Planning 34, no. 3: 160–72. Watkins, Susan Cotts. 2004. Navigating the AIDS epidemic in Rural Malawi. Population and Development Review 30, no. 4: 673– 705. WHO. 2001. Global prevalence and incidence of selected curable sexually transmitted infections: Overview and estimates. World Health Organization. http://www.who.int/hiv/pub/sti/who_hi v_aids_2001.02.pdf Williams, Jill R. 2010. Doing femist demography. International Journal of Social Research 13, no. 3: 197– 210. Williams, Jill R., Enid J. Schatz, Benjamin D. Clark, Mark A. Collinson, Samuel J. Clark, Jane Menken, Kathleen Kahn, and Stephen M. Tollman. 2010. Improving public health training and research capacity in Africa. Global Health Action 3: 5287. Willis, Gordon Bruce. 2005. Cognitive interviewing: A tool for improving questionnaire design. Thousand Oaks, CA: Sage.

824


Wolff, Brent, Ann K. Blanc, and John Ssekamatte-Ssebuliba. 2000. The role of couple negotiation in unmet need for contraception and the decision to stop childbearing in Uganda. Studies in Family Planning 31, no. 2: 124– 37. Yoder, P. Stanley, Papa Ousmane Camara, and Baba Soumaoro. 1999. Female genital cutting and coming of age in Guinea. Calverton, MD: MacroInternational Inc. http://www.measuredhs.com/ publications/publication-qrs2-qualitative-research-studies.cfm


Re´sume´ La compre´hension du genre en Afrique est essentielle pour l’e´laboration de politiques et d’interventions autour de questions cle´s de la sante´ reproductive comme le VIH/sida et la mortalite´ maternelle – des questions qui sont particulie`rement sensibles pour le continent et fortement lieés a` ` la fin des anneés 90, l’ajout de questions aux enqueˆtes de´mographiques l’ine´galite´ entre les sexes. A et de sante´/MEASURE (DHS) pour obtenir des donneés sur l’habilitation et l’autonomie des femmes a e´largi la possibilite´ d’examiner le rapport entre le genre et la sante´ reproductive. Ces questions permettent d’obtenir des informations tre`s utiles sur les tendances et sur les perceptions, au niveau de chaque individu interroge´, des associations entre les ine´galite´s entre les genres et la sante´. L’habilitation, le statut et l’autonomie des femmes de´pendent largement de syste`mes contextuellement lie´s au genre. Cependant, des e´tudes qualitatives comple´mentaires pour valoriser et contextualiser ces donneés renforceraient conside´rablement les analyses. Cet article pre´sente quelques exemples de la manie`re selon laquelle de tels me´langes de me´thodes peuvent ame´liorer les compre´hensions du genre et de la sante´ reproductive en Afrique, en valorisant les questions incluses dans les enqueˆtes, en traçant les grandes lignes de la me´thode d’analyse et d’interpre´tation des donneés DHS et en apportant un ećlairage aux processus et aux mećanismes qui sous-tendent les expe´riences de´termineés par le genre. De plus, ces travaux pourraient contribuer a` ame´liorer les enqueˆtes futures sur le genre et la sante´ reproductive.

Resumen ´ frica es fundamental para desarrollar polı´ticas y disenãr Entender la diferencia de geńero en A programas de intervencioń para solucionar problemas ba´sicos relacionados con la salud reproductora, tales como el VIH y el sida, y la mortalidad materna que son cuestiones especialmente urgentes en el continente africano y en gran medida relacionadas con las desigualdades sexuales. Cuando a finales de los noventa se anãdieron preguntas especı´ficas para entender la emancipacioń y autonomıá de las mujeres en el estudio de Encuestas de Demografıá y Salud (programa Measure/DHS), esto supuso mayores oportunidades para analizar las relaciones entre los diferentes sexos y la salud reproductora. Estas cuestiones ofrecen informacioń valiosa acerca de las tendencias y los vıńculos entre las desigualdades sexuales y la salud de cada persona. Sin embargo, la emancipacioń, el estado y la autonomıá de las mujeres dependen en gran medida de los sistemas de geńero en un contexto especı´fico, por este motivo reforzarıá mucho los ana´lisis contar con estudios cualitativos complementarios para validar y contextualizar estos datos. En este artıćulo ofrecemos ejemplos de co´mo un trabajo semejante con me´todos combinados ayudarıá a comprender mejor la ´ frica al validar las preguntas de los estudios, salud reproductora y las diferencias sexuales en A aportar perspectivas sobre co´mo analizar e interpretar los datos del estudio DHS, y destacar los procesos y mecanismos que hay tras estas experiencias de geńero. Al mismo tiempo, este trabajo mejorarıá los estudios futuros sobre los sexos y la salud reproductora.


825

Appendix. DHS questions on women’s status, autonomy and empowerment Questions from DHS-IV-Model B (1997 – 2003) Additional questions not listed cover: education, age at marriage, contraceptive knowledge and use, spouse’s age, education and employment, literacy and media exposure.

Table 1.


Concept All DHS include these women’s status and empowerment indicators Employment and occupation

Control over own earnings (most surveys)

Question on women’s survey

Response coding

Aside from your own housework, are you currently working? As you know, some women take up jobs for which they are paid in cash or kind. Others sell things, have a small business or work on the family farm or in the family business. Are you currently doing any of these things or any other work? Have you done any work in the last 12 months? What is your occupation, that is what kind of work do you do? Do you work mainly on your own land or on family land, or do you work on land that you rent from someone else, or do you work on someone else’s land?

Yes/No

Do you do this work for a member of your family, for someone else, or are you self employed?

For family member For someone else Self-employed

(Open-ended) Own land Family land Rented land Someone else’s land

Are you paid or do you earn in cash or Cash only kind for this work or are you not paid at Cash and kind In kind only all? Not paid Who mainly decides how the money you earn will be used?

Respondent Husband/partner Respond./husband/ partner jointly Someone else Respondent and someone else jointly

On average, how much of your household expenditures do your earnings pay for: almost none, less than half, more than half or all?

Almost none Less than half About half More than half All None, her income is all saved

826


Table 1 – continued Concept


Questions on all DHS 1999/2000 and later Women’s participation in household decisions

Question on women’s survey

Who in your family usually has the final say on the following decisions: Your own healthcare Making large household purchases Making household purchases for daily needs Visits to family or relatives What food should be cooked each day

Response coding

Respondent Husband/partner Respondent/husband/ partner jointly Someone else Respondent/someone else jointly Decision not made/not applicable

Women’s attitudes toward wife-beating by husbands

Yes/No/Don’t know Sometimes a husband is annoyed or angered by things that his wife does. In your opinion, is a husband justified in hitting or beating his wife in the following situations: If she goes out without telling him? If she neglects the children? If she argues with him? If she refuses to have sex with him? If she burns the food?

Women’s opinions on whether a woman can refuse sex to her husband

Husbands and wives do not always agree on everything. Please tell me if you think a wife is justified in refusing to have sex with her husband when: She knows her husband has a sexually transmitted disease? She knows her husband has sex with other women? She has recently given birth? She is tired or not in the mood?

Hurdles faced by women in accessing healthcare for themselves

Yes/No/Don’t know Many different sectors can prevent women from getting medical advice or treatment for themselves. When you are sick and want to get medical advice or treatment, is each of the following a big problem or not? Knowing where to go Getting permission to go Getting money needed for treatment The distance to the health facility Having to take transport Not wanting to go alone Concern that there may not be a female health provider

Yes/No/Don’t know