Research strategy: quantitative component

The first objective of the quantitative component was to describe characteristics of the study population that were illustrative of women’s life courses and reproductive health: schooling levels, marital patterns, levels of infertility, and demographic and reproductive health indicators. Secondly, outcomes associated with primary and secondary infertility were explored. This section describes data sources, how concepts were operationalised, and data analysis methods.

Quantitative data were collected during the KPS 2000-2005 programme and were double entered and verified in Fox Pro by KPS. Three data sources were used: a baseline census of the study area, a study of antenatal non-attenders (ANA study) nested within the census, and antenatal clinic (ANC) surveillance data from Karonga district (see Table 5 and Figure 7; and Appendix D for survey forms). In brief, the census represented the whole study population, the ANA study provided more detailed data on women who had not given birth in the four years prior to the census (including infertile women), and ANC data came from women who had given birth recently.

Table 5 Overview of quantitative data sources

Data source Participants Data collected

Baseline census Household member reports for all household members in 33 censused villages

Socioeconomic and educational indicators Current marital status

For women: date of last birth and ANC attendance

Antenatal Non- attenders Study (ANA)

All women aged 15-44 in census who had not attended ANC in previous 4 years

HIV status Marital history

Reproductive history , Contraceptive use STI symptoms

Antenatal clinic (ANC) data

Women attending five selected ANC clinics in Karonga district

HIV status Marital history

Figure 6 Diagram of quantitative data sources (not to scale)

4.4.1 Census data

A baseline census was carried out from 2002 to 2005 in order to establish a Continuous Registration System (CRS) of demographic events. The census covered over 30,000 people in 33 villages around Chilumba. All qualitative data were collected in this area. As census data were representative of the study area, they are used to illustrate the broad demographic context, and examine associations between infertility and outcomes such as current marital status and polygyny.

4.4.2 Antenatal Non-Attenders (ANA) study

The ANA study19 was designed to compare ANC non-attenders with ANC attenders on indicators such as HIV status, marital history, and parity for age. It aimed to measure the degree to which ANC HIV surveillance misrepresents HIV prevalence in the female population (Jahn, Ngwira et al. 2004). ANA women were recruited through the baseline census, which asked all women aged 15-45 years whether they had visited an antenatal clinic (ANC) in the past four years. Forty three percent (2949) of women had not, and were subsequently visited at home by ANA study fieldworkers. Study participants

19_{Participants were offered voluntary counselling and testing for HIV, syndromic management of STIs,}

and treatment for anaemia and intestinal worms. Female interviewers administered questionnaires on marital and reproductive history, contraceptive use and age at first sex (interviewers were trained to define this as first penetrative sex).

Study area (Chilumba) Census 2002-2005 N = 31,953

Women without a birth in 4 years prior to census included in ANA study (n=1617) ANC data collection N=5114 In-depth interviews KARONGA DISTRICT

Women who had a birth in the 4 years prior to census (two thirds of women)

In-depth Interviews

consisted of currently infertile women, and women who had not recently given birth for other reasons, such as using contraceptives or not being sexually active. Very few women had had a birth but had not attended ANC (1%). Detailed marital history, contraceptive use, and fertility treatment data enabled identification of infertile women according to several different definitions (see 4.4.4).

The response rate to the ANA study was 80%. Of eligible women who did not take part, 60 refused and 210 were lost to follow-up. Eligible women tended to be quite mobile: by the time ANA study fieldworkers arrived, they had often married elsewhere, divorced, or moved away. If ANA and ANC data were roughly representative of the overall female population of women, their combined prevalence of a characteristic such as ‘being currently divorced’, if adjusted to match the age structure of the census, should have been similar to the prevalence of divorce in the census. These checks were carried out and it was found that the proportion of women divorced was the same in the census as in ANA, yet only 1% of women at ANC were divorced. One would expect the proportion of divorced women to be higher in ANA, suggesting that ANA under- represented divorced women. This supports the conclusion that ANA data are not representative of women who had not recently attended ANC, but is biased towards more settled women.

4.4.3 Antenatal clinic (ANC) surveillance

Data were collected from mothers attending five ANC clinics in Karonga district from 1999-2004. They included one urban district hospital (Karonga), two rural hospitals (one semi-urban (Chilumba), one rural), and two rural health centres. A similar questionnaire to that used in the ANA study was administered. Unlinked anonymous HIV testing was carried out. For ANA and ANC data collection, interviews, specimen collection, anonymisation and dual laboratory HIV testing were carried out using well- established methods. ANC data were not representative of the fertile female population: they represented a sample of clinics and a sample of women using them at that time. Clinics had been dropped systematically from surveillance as voluntary counselling for HIV was introduced, compromising anonymity.

4.4.4 Operationalising definitions

The following definitions of infertility were used in quantitative analyses:

Table 6 Quantitative indicators of infertility

Indicator Definition Data source

Childlessness Ever-married women with no live births by age 45 Census

Perceived infertility Currently using fertility treatment ANA

Primary infertility One year exposure to pregnancy without a live birth/pregnancy ANA, ANC Secondary infertility 5 years exposure to pregnancy without live birth/pregnancy

following live birth

ANA, ANC

Childlessness can be used as a proxy for infertility in married women in populations where several assumptions might hold: that there is early marriage (94% of women in the census aged 25-29 are ever-married), that women aged over 40 years are unlikely to subsequently have a live birth, that there is little voluntary childlessness, and that few women are use contraception before their first birth (only 2% of married nulliparous ANC women had ever used contraception). This was the most accurate definition that census data could support, as exposure to pregnancy could not be calculated. This measure was used to estimate levels of childlessness in the study area.

Cases of infertility in ANA and ANC could be identified more accurately using marital history and contraception data. Absence of live births rather than conceptions was used to indicate infertility, because live births are more accurately reported. This study defined cases of primary infertility as women with one year’s exposure to pregnancy without a live birth or pregnancy. This definition was in line with local definitions of infertility: after a year, lack of pregnancy would usually be considered problematic. Exposure of pregnancy was defined as being married and not using contraception. Being married was thought to be a suitable proxy for regular unprotected sexual activity, at least for cases of primary infertility, because of the desirability of pregnancy at the start of marriage (discussed in Chapter 5). However, this measure probably overestimates secondary infertility in older women. Their long birth intervals might reflect gaps in exposure to pregnancy rather than infertility, for instance, through not being sexually active. For secondary infertility, the definition employed was ‘five years exposure without a live birth following the last live birth’, which follows demographic

convention (Larsen and Raggers 2001a) and allows for a period of infecundibility following childbirth.

4.4.5 Quantitative analysis

Quantitative data analysis was carried out using Stata version 9. Descriptive data from the census, ANC and ANA were used to quantify aspects of women’s life courses and estimate the level of childlessness in the census area.

Outcomes of interest when looking at effects of infertility on women’s lives were: - Positive HIV status

- Having been married more than once - Being polygynously married

The next step was to decide how to use the available data sources to compare outcomes between exposure groups. Neither ANA nor ANC data reflected the general female population, and the census, which was representative of the female population, did not collect sufficiently detailed marital history data to define cases of infertility. Women in the ANA and ANC datasets were therefore divided according to their fertility status to generate the ‘exposure categories’ for which measures of relative, rather than absolute, risk could be calculated:

- Nulliparous ANA women - Parous ANA women - Nulliparous ANC women - Parous ANC women

- ANA women, primary infertility (1 year) - ANA women, secondary infertility (5 years) - ANA women, using traditional fertility treatments

Crude outcome rates were calculated for each exposure group. These were then indirectly standardised for age cohort and marital status against a standard population (the census population structure and outcome rates from overall ANC data). SMRs20 were then calculated (the ratio of observed to expected events) to give a measure of relative risk of each outcome compared to the standard population.

Year of birth rather than age at interview was used, because data were collected over several years. In order to determine exposure category, data on marital duration and contraceptive use were used. Marital duration was the sum of current and previous marriages. Start and end dates were available for ANA women’s first marriages if they had been married more than once. Gaps between marriages were not counted unless women had more than two previous marriages, in which case date of first marriage marked the start of marital duration, and date of interview (if currently married) or date of last divorce marked the end of marital duration. Women who did not contribute HIV data were excluded from the analysis.