AMANHI study indicated that low-income and middle-income countries relied on low-quality to generate modeled mortality estimates. In this case, the burden of estimates of maternal deaths relied heavily on diverse sources such as civil registrations, population-based studies, and country census. The diversity of these sources means that the burden of estimates of maternal deaths is likely to be inaccurate. Therefore, AMANHI wanted to produce a standard definition of the burden, timing, and causes of maternal death in South Asia and sub-Saharan Africa. The standard definition was going to show the causal relationship between socioeconomic factors such as low-income and high maternal death. The background of the AMANHI study showed inconsistent sources of data lead to inaccurate burdens such as timing and causes of maternal deaths. The absence of quality data (dependent variable) leads to inaccurate estimates about the burden and causes of maternal deaths in South Asia and sub-Sahara Africa. Therefore, the purpose of the study was to create a prospective data that can be used to the causal relationship between socioeconomic factors and maternal deaths in South Asia and sub-Sahara Africa. The purpose of this study was supported by sufficient evidence which how maternal mortalities in south Asia and sub-Sahara Africa remain considerably high. For instance, many countries in the regions have not achieved Millennium Development Goals (MDGs) on maternal mortalities and child survival. More than three-quarters of global deaths occur in and sub-Saharan Africa (Girum & Wasie, 2017). The case of South Asia and sub-Sahara is caused by the lack of standardized definitions and inclusive data that offer population-based data on mortality rates (MacDorn et al., 2017). Lack of a standardized framework leaves data gaps that prevent individuals from the Asia and African regions from understanding the burdens and causes of maternal deaths, such as socioeconomic factors (Girum & Wasie, 2017). This evidence showed the need for population-based data that can be used to describe the causal relationship between socioeconomic factors and maternal deaths. The findings of this study provide a concrete framework for dealing with maternal deaths. Data obtained in the study show how socioeconomic factors such as poverty lead to high rates of maternal deaths (MacDorn et al., 2017). The results of the research are an addition to the growing evidence of the relationship between maternal mortalities and socioeconomic factors such as level of income.
Research Design
AMANHI study was a prospective cohort study that was conducted in 11 community-based research sites in sub-Saharan Africa and South Asia. Cohort studies are types of research used to determine the causes and risk factors of disease (Beck, 2016). Cohort studies involve large pools of participants who are examined to find patterns of a particular disease (Beck, 2016). The prospective study, therefore, offered an empirical framework of examining the causal relationship between socioeconomic factors and maternal deaths. The study was conducted between July 2012 and Feb 2016 and was population-based surveillance of reproductive women between 15 and 49 years. Pregnancies were identified and were followed until birth and 42 days after birth. A uniform protocol was implemented across the sites. The researchers held to join to train assistants and harmonize the implementation of the research procedure. All sites had population-based surveillance on reproductive women in geographically defined areas. Field workers were sent to visit the reproductive women every 2-3 months to collect information about the social demographics behind maternal deaths. In Zambia, this data was obtained during the first booking at maternal clinics. The women were then followed at home.
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Verbal autopsy was done to identify issues directing the cause of death. Verbal autopsy, according to MacDorn et al. (2017), is a method that is used to ascertain the causes of death that are based on interviews. Caregivers are asked to give their accounts regarding the circumstance, signs, and symptoms that preceded death. Verbal autopsy was done to all cases of maternal deaths, and the data were analyzed in tables based on WHO verbal autopsy standard tools. Verbal autopsy involved narratives about the events leading to death and the timing of death. The narratives were then validated by a review of health records. These strategic steps were intended to ascertain that deaths were pregnancy-related or not and ensure the productivity of results. These strategies were used to minimize bias (Beck, 2016). Furthermore, data management software was installed at each to ensure consistency and logic check of data. The management team also reviewed data regularly and transferred to another team at WHO Geneva for consistency checks. The Geneva team also held site visits to oversee the collection and implementation of data. These quality assurance checks played a significant role in ensuring the validity and reliability of data (Beck, 2016).
Population and Sample
The sample size involved 278186 pregnant women who would provide estimated burdens of maternal mortality. These pregnancies were identified across the study sites. The sample size was spread across south Asia and sub-Saharan Africa. The sample size was large and allowed the project management to quantify single causes of maternal deaths. The sample gave the researcher a higher degree of precision in establishing high-quality data regarding maternal deaths. The study involved adults who lived with the deceased in the period preceding death. Only participants who could give information about the events leading to death were involved in the study.
References
Beck, C. T. (2016). Routledge international handbook of qualitative nursing research . New York: Routledge.
Alliance for Maternal and Newborn Health Improvement (AMANHI) mortality study group. (January 01, 2018). Population-based rates, timing, and causes of maternal deaths, stillbirths, and neonatal deaths in south Asia and sub-Saharan Africa: a multi-country prospective cohort study. The Lancet. Global Health, 6, 12, 1297.
Girum, T., & Wasie, A. (2017). Correlates of maternal mortality in developing countries: an ecological study in 82 countries. Maternal health, neonatology and perinatology , 3 , 19.
MacDorman, M. F., Declercq, E., & Thoma, M. E. (2017). Trends in Maternal Mortality by Sociodemographic Characteristics and Cause of Death in 27 States and the District of Columbia. Obstetrics and gynecology , 129 (5), 811–818.
