Living with infertility: experiences among urban slum population in Bangladesh

This paper explores the perceived causes of infertility, treatment-seeking for infertility and the consequences of childlessness, particularly for women, among a predominantly Muslim population in urban slums of Dhaka in Bangladesh. In-depth interviews were conducted with 60 women and GO men randomly selected from Urban Surveillance System clusters of the international Centre for Diarrhoeal Disease Research, Bangladesh. Case studies of 20 self-perceived infertile women who had previously participated in a study on the prevalence of sexually transmitted diseases and other reproductive tract infections were taken, and three traditional healers were interviewed as key informants. In both groups of respondents, the leading ca uses of infertility were perceived to be evil spirits and physiological defects in women and psychosexual problems and physiological defects in men. Herbalists and traditional healers were considered the leading treatment option for women, while for men it was remarriage, followed by herbalists and traditional healers. Childlessness was found to result in perceived role failure, with social and emotional consequences for both men and women, and often resulted in social stigmatisation of the couple, particularly of the woman. Infertility pla ces women at risk of social and familial displacement, and women clearly bear the greatest burden of infertility. Successful programmes for dealing with infertility in Bangladesh need to include both appropriate and effective sources of treatment at community level and community-based interventions to demystify the causes of infertility, so that people know why infertility occurs in both men and women and and where best to seek care

Improving performance of the Tariff Method for assigning causes of death to verbal autopsies

Background: Reliable data on the distribution of causes of death (COD) in a population are fundamental to good public health practice. In the absence of comprehensive medical certification of deaths, the only feasible way to collect essential mortality data is verbal autopsy (VA). The Tariff Method was developed by the Population Health Metrics Research Consortium (PHMRC) to ascertain COD from VA information. Given its potential for improving information about COD, there is interest in refining the method. We describe the further development of the Tariff Method. Methods: This study uses data from the PHMRC and the National Health and Medical Research Council (NHMRC) of Australia studies. Gold standard clinical diagnostic criteria for hospital deaths were specified for a target cause list. VAs were collected from families using the PHMRC verbal autopsy instrument including health care experience (HCE). The original Tariff Method (Tariff 1.0) was trained using the validated PHMRC database for which VAs had been collected for deaths with hospital records fulfilling the gold standard criteria (validated VAs). In this study, the performance of Tariff 1.0 was tested using VAs from household surveys (community VAs) collected for the PHMRC and NHMRC studies. We then corrected the model to account for the previous observed biases of the model, and Tariff 2.0 was developed. The performance of Tariff 2.0 was measured at individual and population levels using the validated PHMRC database. Results: For median chance-corrected concordance (CCC) and mean cause-specific mortality fraction (CSMF) accuracy, and for each of three modules with and without HCE, Tariff 2.0 performs significantly better than the Tariff 1.0, especially in children and neonates. Improvement in CSMF accuracy with HCE was 2.5 %, 7.4 %, and 14.9 % for adults, children, and neonates, respectively, and for median CCC with HCE it was 6.0 %, 13.5 %, and 21.2 %, respectively. Similar levels of improvement are seen in analyses without HCE. Conclusions: Tariff 2.0 addresses the main shortcomings of the application of the Tariff Method to analyze data from VAs in community settings. It provides an estimation of COD from VAs with better performance at the individual and population level than the previous version of this method, and it is publicly available for use