An application of multiple logistic regression for identifying lipid profile changes towards assessing maternal and fetal outcomes - Rosaiah, K.; Kolli, Naga Saritha; Sanjeeva Rao, N. S. (International Journal Of Community Medicine And Public Health, 2020)
Background: The millennium development goals encourage governments to address and reduce various developmental issues, two of the important ones being maternal and child health. The one of the important causes of maternal mortality in India is pregnancy induced hypertension (PIH) and present study is to identify the relationship between disturbed lipid profile and preeclampsia its effect on fetal and maternal outcome. Methods: This was a descriptive cross-sectional study done on data of maternal care and outcomes from the NRI General Hospital, Guntur district in the year 2013. Multiple logistic regression analysis is applied and results are adjusted to covariates maternal age and gravida. Results: Systolic blood pressure, diastolic blood pressure of normal group (n=50) and PIH group (n=60) are 116.08±7.77, 76.08±4.93, and 165.66±16.8 105.5±14.07 respectively. Birth weights of infants in normotensives and PIH group are 2.85±0.33 and 1.93±0.659 respectively. Percentages of fetal and maternal complications in PIH group are 88.33% and 25%. Still births are present in 31.66% of PIH cases. Mean and SD of gestational age in weeks in normal and PIH groups are 37.92±1.94 and 34.36±3.44 respectively. Conclusions: The model showed significant association between the selected independent variable, covariates and outcomes. The study demonstrates that multiple logistic regression may be applied to medical data in developing predictor models which are useful in clinical settings.