We aimed to find the socio-economic and reproductive factors which are related to the women’s economic condition. For this, we used BDHS data where the wealth index was categorized into five groups. In urban areas, the study has found highest numbers of poor women in Dhaka Division as people from different areas have come here and searched for employment. Similarly, in rural areas, the highest number of poor women (about 85%) have found in Rangpur Region. Extreme poverty and powerlessness have always been inseparable misfortunes. With the Government’s initiative to reduce poverty by 15% by 2021 and various microfinance initiatives, there have been certain improvements.
The wealth index is highly associated with BMI of women (Neuman, 2013). BMI has a positive loading with wealth index as low BMI affected most. All obese and adult women are associated with higher household (Bishwajit, 2017).
In the multifactor analysis, it was found that marital status has a negative relationship with wealth index. The same thing happens to household member also. The number of household members is also shown the negative relation with wealth index. Menopausal status and contraceptive use have no significant loadings with wealth index. And in both urban area and rural area people are interested in the contraceptive. In Bangladesh, the use of contraceptive is increasing rapidly and most of the married women are willing to use it. (Khan et al, 2014). Another study found that employed women are more interested to use contraceptive than unemployed women (Islam, 2016).
The number of children has a negative loading with wealth index. We found that rural people are much poor than urban people. Age at first birth has positive loading with wealth index.
In rural Bangladesh, the age at first birth is very low because of rural sociocultural (Haque et al., 2009). There is no significant difference between the working status of rural and urban areas women. But our Multifactor analysis shows the negative loadings with wealth index. TV watching has positive loadings with wealth index but this study has found contradictory result i.e.
, a multifactor corresponding analysis shows that those who do not watch Television (TV) at all, mostly affected by wealth index. Women education and their husband education both have positive loadings with wealth index. And in both cases, higher education has most positive relation according to MCA (Multiple Correspondence Analysis). Considering the group integration, it was found Educational status, Household member and Husband education in the socio-demographic group (Group 2) were positively associated with Menopausal and Age at first birth of reproductive group (group 1).