Koustuv Dalal, Jahan Shabnam, Johanna Andrews-Chavez, Lena B. Mårtensson and Toomas Timpka
Economic empowerment indicators assessed included respondent's working status, employment status, association with any microfinance program, and decision making on spending money. Working status was assessed by whether the respondent was employed or not. Association with microfinance program was assessed by whether the respondents had a microfinance loan or not. Employment status had three alternatives: whether respondent worked year around, worked seasonally, or worked occasionally. Seasonal work is say for example paddy filed work during monsoon season to cultivate rice.
Every year more than half a million women die from preventable complications caused by childbirth or from pregnancy-related issues. The large majority (99%) of these maternal deaths occur in low-income countries. In Bangladesh, with a population among the poorest in the world, maternal mortality, as well as associated maternal morbidity, is a serious public health concern. Currently, the maternal mortality ratio is one per 350 births. Along with the United Nations, the government of Bangladesh is committed to achieving the Millennium Development Goal (MDG) 5, i.e., to reduce the maternal mortality ratio by 75% between 1990 and 2015.
Circumstances acquiescent to intervention by skilled health providers are engaged in the casual mechanisms for about 80% of maternal deaths, and currently, the main strategy for reducing maternal mortality has been to scale up access to delivery care during the time of delivery. While skilled birth attendance and emergency obstetric care are essential to securing significant reductions in maternal mortality, health service extension by itself is not sufficient. In most home deliveries in Bangladesh, such services are not utilized. The reasons for this under-utilization have not been satisfactorily investigated. The relationships between economic empowerment and improved health status in terms of child mortality, nutrition, immunization coverage, and contraceptive use have been documented in Bangladesh. However, women's economic situation and utilization of child delivery care services is a salient problem that has received less attention.
Present evidence suggests that the available maternal health services are not utilized appropriately in regions where the need for such services is most prevalent, such as areas with deprived populations. Due to gender inequalities, women in poor populations often discover themselves even further disadvantaged within the deprived population, as a result of being the poorest among the poor and the least educated within the insufficiently educated. However, economic empowerment of women in relation to health care utilization is not well explored. The aim of the study is to investigate the associations between women's economic empowerment and their utilization of maternal health services in Bangladesh.
The study was based on a cross-sectional design, implemented in Bangladesh through a nationally representative household survey during January-August 2007. Data were collected from 10,996 women aged 15-49 surveyed from 10,400 households through a nationally representative household survey using a structured questionnaire.
The survey involved multistage cluster sampling and was based on the 2001 population census enumeration areas (EAs) with population and household information. EAs were used as primary sampling units (PSUs) for the whole survey. Each PSU had 100 households with locational maps and geographical boundaries. In total, 361 PSUs (227 in rural areas and 134 in urban areas) were randomly selected from the six divisions - Barisal, Chittagong, Dhaka, Khulna, Rajshahi, and Sylhet.
During January to March 2007, a household listing operation was carried out in all PSUs before the main survey, and the resulting lists of households served as the sampling frame for the selection of households in the second stage. In the next stage, 30 households were selected from each PSU, using an equal probability systematic sampling technique in relation to the 2001 population census. Finally, 10,819 households were initially selected from the sample clusters for the survey.
All ever-married women of reproductive age (15-49 years) who slept in the chosen households the night before the survey were eligible to participate in the survey. At the next stage 10,400 households were occupied and selected for the study. From these selected households, 11,178 eligible women aged 15-49 years were identified and 10,996 were interviewed with a response rate of 98%.
Women with a history of delivery of at least one child were included in the current study (N = 4925) constituting 45% of the total 10,996 women respondents of the whole survey.
Description of the variables of interest
The utilization of health facilities during the last delivery was assessed by the place of delivery: delivery at home mainly without utilizing the delivery care services and delivery at health care facilities. For this study, health facilities include government hospitals, private hospitals/clinics, NGOs, and other health facilities.
The variables were age (groups divided in to seven categories 15-19, 20-24, 25-29, 30-34, 35-39, 40-44, and 45-49), residency (urban or rural), the level of education of the women and the partner (no education, primary education, secondary education, and higher education), religion (Muslim or non-Muslim), and divisional residence within Bangladesh (Dhaka, Barisal, Sylhet, Rajshahi, Chittagong, and Khulna).
In patriarchal societies like Bangladesh, sex of the household head is important as it often decides the kind of health care the house members receive. Therefore, the current study also considered sex of household head.
Economic status of the respondents was defined in five quintiles: poorest, poorer, middle, richer, and richest. The economic status of the respondents were measured based on the wealth index. Wealth index is a widely used measurement of economic status used to ascertain the equity of health programs in publicly or privately provided services. The main objectives of wealth index are to measure ability to pay for health services and the distribution of services among the poor. Wealth index was validated and used in several demographic and health surveys in different countries. The wealth index is a composite measure of the cumulative living standard of a household. It is calculated by using data on a household's ownership of selected assets, e.g., radio, televisions, and bicycles, materials used for construction of house, types of water-access, and use of sanitation facilities. Wealth index uses a generated statistical procedure known as the principal components analysis and places individual households on a continuous scale of relative wealth. The scale is standardized in relation to a standard normal distribution with a mean of zero and a standard deviation of one. These standardized scores are then used to create the groups that define wealth quintiles as: poorest, poorer, middle, richer, and richest. The wealth index used in Bangladesh was introduced by Rutstein and Johnson (2004) and includes any item that may reflect economic status, specifically most household assets and utility services, including country-specific items.
Neighborhood socioeconomic (NSE) status was measured by whether the respondent lived in a less or more disadvantaged socioeconomic neighborhood. The NSE index comprised four variables: proportion of respondents living in rural areas, proportion of respondents living in slum areas, proportion of respondents living below the poverty level (below the 20% quintile), and the proportion of respondents who are uneducated. This methodology has been used by many others studying the effect of neighborhood socioeconomic status on health. The scores generated from the continuous index were used to classified neighborhoods into two categories: (i) more disadvantaged and (ii) less disadvantaged socioeconomic neighborhood status.
Economic empowerment indicators assessed included respondent's working status, employment status, association with any microfinance program, and decision making on spending money. Working status was assessed by whether the respondent was employed or not. Association with microfinance program was assessed by whether the respondents had a microfinance loan or not. Employment status had three alternatives: whether respondent worked year around, worked seasonally, or worked occasionally. Seasonal work is say for example paddy filed work during monsoon season to cultivate rice. To assess the decision-making ability of the respondent in the household, respondents were asked who decides how to spend money. The alternatives were respondent alone, shared with husband and other member of the household.
The survey procedure (e.g., organization and sampling methods) and instruments used in the study received ethical permission from the Institutional Review Board of ORC Macro Inc, who provided the main scientific support for the whole survey. The permission to use these data was obtained from Measure Demographic and Health Survey, the legal owner of the survey data under the main donor agency, USAID through proper project applications.
This study is based on an analysis of existing survey data with all information that could be used to identify the respondents being removed. The field interviewers for the survey obtained informed consent from the respondents in this study and all questions were asked in close confidentiality. The respondents had the autonomy to leave the study at any stage.Ethical recommendations: The study has received ethical permission from the Institutional Review Board of ORC Macro Inc.
Descriptive statistics were used to display differences in proportions of home delivery between population strata. Unadjusted logistic regressions were thereafter used to assess the independent contribution of demographics (individual and family level) and economic variables (individual and group level) in predicting home delivery. For assessing confounding effects, multivariate logistic regression analysis was employed in the adjusted model. The magnitude and direction of association were expressed through odds ratios and significant levels expressed as P values. Statistical significance was considered at P < 0.05.
Courtesy : International journal of Preventive Medicine.