91.6 (79.4–105.1) 161.0 (141.6–182.3) 190.2 (166.2–216.6) 133.3 (113.8–155.4) 56.4 (45.3–69.7) 124.0 (116.0–1312.4) 0.83 (0.76–0.89) RIR (95% CI) C1/C2 1.81 (1.59–2.08) 0.70 (0.63–0.77) 0.71 (0.64–0.77) 0.44 (0.35–0.52) 0.68 (0.55–0.79) Age bracket (years) 15–19 20–24 25–29 30–34 ≥ 35 Total 14 20 25 6 5 70 84.4 177.0 185.3 104.2 130.6 681.5 165.8 (98.1–257.9) 113.0 (71.0–171.4) 134.9 (89.5–196.0) 57.6 (23.3–119.8) 38.3 (14.2–83.2) 102.7 (80.7–129.0) 196 240 219 140 83 878 2139.9 1491.0 1151.6 1050.4 1470.8 7079.7 CI = confidence interval; RIR = relative inclusion ratio; HIV = Human Immunodeficiency Virus BMC Public Health 2008, 8:309 http://www.biomedcentral.com/1471-2458/8/309 Table 3: Fertility rates and relative inclusion ratios (RIR) for HIV positive and HIV negative women by age in the urban area of Cameroon, 2004. HIV positive women HIV negative women Number of births (A1) Woman-years at risk (B1) Fertility rate (95% CI) C1 = (A1/B1)*1000 Number of births (A2) Woman-years at risk (B2) Fertility rate (95% CI) C2 = (A2/B2)*1000 Overall, the fertility rate in all HIV positive women (rural and urban combined) was 118.7 births per 1000 woman- years (95% CI 98.4 to 142.0) compared to 171.3 births per 1000 woman-years (95% CI 164.5 to 178.2) for HIV negative women. Consequently, the summary RIR was 0.69 (95% CI 0.62 to 0.75). These values of fertility rates are self-weighted in terms of age and rural-urban differ- ences because the sample represents all women of repro- ductive age in Cameroon. Discussion This study compared fertility rates in HIV-infected and uninfected women of reproductive age using population- based data. Our findings indicate that fertility rates are lower in HIV infected women compared to uninfected women in Cameroon. Our finding of low fertility in HIV positive women is con- sistent with reports from other authors [3,4]. We found low fertility rates in HIV positive women of all age groups but for urban HIV-infected teenagers (that is, 15–19 year olds) who had a higher fertility rate than their correspond- ing HIV negative counterparts in cities. We could not find any suitable explanation to this finding. However, since the teenagers in rural areas were similar to other adult women in terms of their RIR, the cause is unlikely to be biological. We therefore attributed the high fertility in urban HIV-infected teenagers to differences in sexual and reproductive attitudes and practices. Monitoring of HIV epidemic via antenatal sentinel surveillance requires regu- lar adjustments for many factors such as the differences in distribution of HIV across different age groups and differ- ent sub-populations, and differences in fertility rates between the infected and the uninfected women [26]. Adjustment for fertility rates is an important factor because modest changes in fertility can have profound effects on the validity of estimates from pregnant women [27]. Nicoll et al suggested that adjusting for the differ- ences in fertility rates was sufficient in countries with over- whelming epidemics where the infection was transmitted through one source (heterosexual route) and many peo- ple are unaware of their HIV status [2]. The authors argued that it might be possible to use summary RIR in wider geo- graphical area such as Sub-Saharan Africa. Our study reports the summary RIR for Cameroon. Since the study population was a representative sample of the all Cam- eroon women of reproductive age, our RIR is self- weighted for regional and age differences. Eighty three percent (83%) of Cameroonian women attend at least one antenatal visit during pregnancy [22]. However, the differences in utilization of antenatal services by HIV-pos- itive and HIV-negative women could introduce bias in the ANC-based prevalence estimates. Our study used fertility rates (number of births per 1000 woman years of exposure over 36 months) instead of live birth rates (number of live births per 100 woman years of exposure) as reported by Nicoll et al [2], because we con- sider that all pregnant women are equally likely to be tested for HIV infection irrespective of the birth outcome (dead or live births). Desgrées du Loû et al used parity as a proxy for fertility rate [28]. Parity is a cumulative meas- ure of fertility and is insensitive to recent changes in fertil- ity. In Zambia, ANC-based HIV estimates were found to substantially underestimate declines in HIV prevalence in the general population [29]. This was partly explained by changes in fertility-related behaviours among young women. We found a summary RIR of 0.69 which is lower than that reported by other authors [4,28,30]. Nicoll et al reported a summary RIR of 1.03 for London and 0.80 for women else where in England and Wales [2]. The differences may be explained by socio-cultural differences of the two pop- ulations. Desgrées du Loû et al in Ivory Coast reported a summary RIR of 0.84 which is higher than our summary Page 5 of 7 (page number not for citation purposes)