dc.contributor.author |
Dutta, T. |
|
dc.contributor.author |
Dwivedi, L.K.D. |
|
dc.date.accessioned |
2016-10-21T08:28:58Z |
|
dc.date.available |
2016-10-21T08:28:58Z |
|
dc.date.issued |
2016 |
|
dc.identifier.citation |
Dutta, T. and Dwivedi, L.K.D. 2016. Association between Maternal Health Status and Birth Weight of Children among Young Mothers in India using Missing Case Analysis. 3rd International Conference on Social Sciences (3rd ICSS), 30th September - 01st October 2016, Research Centre for Social Sciences, Faculty of Social Sciences, University of Kelaniya, Sri Lanka. p 65. |
en_US |
dc.identifier.uri |
http://repository.kln.ac.lk/handle/123456789/14686 |
|
dc.description.abstract |
In low income countries like India, birth weight is often not reported by mothers or family members due to
not knowing or not noting down the weight at the time of birth. Thus, there are a good number of birth weight
cases missing from large scale demographic surveys like the National Family Health Survey. In the National
Family Health Survey, Round III, 2005-06, around 59% cases of birth weight of children are missing due to
not knowing or not noting down the weight at the time of birth. Therefore, it poses several limitations for
researches conducted on birth weight of children using NFHS dataset. One such major limitation is the
biasness of the results due to the unavailability of cases. The present study aims to address the issues of
missing data in the birth weight variable in NFHS, Round III, using a simple regression imputation method.
Imputation is a method to fill in missing data with plausible values to produce a complete data set. In the
present paper, regression imputation is chosen for replacing the missing cases, as it is a very simple method
and efficiently deals with the missing cases. Also, the study attempts to examine the relationship between
birth weight and maternal health status and health-seeking behavior, along with other socio-economic
correlates. This is done by first imputing the missing cases of the birth weight variable, and then examining
its relationship with various socio-economic and demographic factors. It compares the likelihood of low and
high birth weight babies against the normal birth weight with the same set of independent variables using the
multinomial logistic regression. The results of imputation imply that any analysis done with the birth weight
variable which has only 40 per cent cases available, ignoring the missing values would yield biased results.
It would render more emphasis on the religion, sex of child and BMI of mothers as the significant
determinants. However, after imputation, the pattern of significance changes and more important socioeconomic and cultural determinants gain importance. It also suggests that imputing missing cases for a
variable gives the model a better fit. Looking at the results of multinomial logit model, one can infer from
this study that healthcare utilization during pregnancy is not the sole determinant of a healthy pregnancy
outcome. The health status and lifestyle of mothers in their prime reproductive years is of immense
importance in determining the birth weight of a child. |
en_US |
dc.language.iso |
en |
en_US |
dc.publisher |
Research Centre for Social Sciences, Faculty of Social Sciences, University of Kelaniya, Sri Lanka |
en_US |
dc.subject |
National Family Health Survey |
en_US |
dc.subject |
birth weight |
en_US |
dc.subject |
missing cases |
en_US |
dc.subject |
imputation |
en_US |
dc.subject |
maternal health status |
en_US |
dc.subject |
maternal health-seeking behavior |
en_US |
dc.title |
Association between Maternal Health Status and Birth Weight of Children among Young Mothers in India using Missing Case Analysis |
en_US |
dc.type |
Article |
en_US |