Socio-economic determinants of low birth weight in Bangladesh: A multivariate approach

Socio-economic determinants of low birth weight in Bangladesh: a multivariate approach.

Though the health situation of Bangladesh has improved substantially over the years, the low birth weight (LBW) rate is still pretty high. The principal focus of this study was to ascertain the significant determinants for LBW. One hundred and eight LBW babies were compared with 357 normal birth weight babies. Out of 20 possible risk variables analyzed, 9 were found significant when studied sep...

Socio-Economic and Nutritional Determinants of Low Birth Weight in India

BACKGROUND Low birth weight (LBW) is an important risk factor for childhood morbidity and mortality, consequently an important public health concern. AIM This study aims to identify significant socio-economic and nutritional determinants associated with LBW in India. MATERIALS AND METHODS Data from 2005 to 2006 National Family Health Survey-3 (NFHS-3) of India was analyzed. A total of 20,94...

Socio-biological determinants of birth weight.

A study on a few selected socio-biological determinants of birth weight was conducted at a rural project hospital in Haryana. Records of 2292 singleton live births over a period of two years (1985-1987) were analysed, by bivariate and multivariate methods. The mean birth weight of the infants was 2715 g (S.D. 453). Mean birth weight of male infants was 92 g more than female infants. Literacy le...

Relationship between Structural and Intermediate Social Determinants of Health and Low Birth Weight: A Path Analysis

Background: Low birth weight is one of the most important health indicators for assessing the status of newborns in every country. It is, therefore, necessary to identify factors associated with this adverse pregnancy outcome. This study was conducted to determine predicting factors associated with low birth weight using path analysis. Methods:</stron...

Determinants of low birth weight in a Block of Hooghly, West Bengal: A multivariate analysis