Prediction of low birth weight (LBW) among smokeless tobacco-using pregnant mothers by using stepwise logistic regression model

INTRODUCTION: Children's health is tomorrow's wealth is one of the WHO's slogans of the recent years. However, children's health is to a great extent determined by factors that operate in utero, well before they are born. Newborns falling in the category of low birth weight (LBW)...

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Published in:Indian Journal of Health Sciences and Biomedical Research KLEU
Main Authors: Praveen Ganganahalli, Satish V Kakade, Jyotsna A Patil, Asha Pratinidhi
Format: Article
Language:English
Published: Wolters Kluwer Medknow Publications 2024-01-01
Subjects:
Online Access:http://www.ijournalhs.org/article.asp?issn=2542-6214;year=2024;volume=17;issue=1;spage=21;epage=25;aulast=Ganganahalli
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author Praveen Ganganahalli
Satish V Kakade
Jyotsna A Patil
Asha Pratinidhi
author_facet Praveen Ganganahalli
Satish V Kakade
Jyotsna A Patil
Asha Pratinidhi
author_sort Praveen Ganganahalli
collection DOAJ
container_title Indian Journal of Health Sciences and Biomedical Research KLEU
description INTRODUCTION: Children's health is tomorrow's wealth is one of the WHO's slogans of the recent years. However, children's health is to a great extent determined by factors that operate in utero, well before they are born. Newborns falling in the category of low birth weight (LBW) carry relatively greater risks of perinatal and neonatal morbidity and mortality and substandard growth and development in the later life. OBJECTIVES: The objective of the study was to study birth weight pattern of newborn babies and to find determinants of LBW among babies born to women using Mishri during pregnancy and to construct predictive model for LBW using multiple binary regression. MATERIALS AND METHODS: A cross-sectional study was conducted in the obstetric wards on women admitted for delivery and using Mishri (form of Tobacco), and they were compared with the nonusers of any form of tobacco. Details of pregnancy and delivery followed by the estimation of serum levels of cotinine using ELISA technique were collected among both groups. STATISTICAL ANALYSIS USED: Statistical analysis used multiple binary regression model and tests of significance. RESULTS: LBW is eight times more commonly seen among users of Mishri compared to nonusers of Mishri. As the cotinine level increases, there is a significant decrease in birth weight (relative risk: 4–10 times) was observed. CONCLUSIONS: Increase in cotinine levels and decrease in birth weight explain the dose–response relationship between the use of tobacco (Mishri) and adverse pregnancy outcomes (LBW). This can be applied to assess the risk among pregnant women who are using Mishri at their first antenatal care visit.
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spelling doaj-art-bb7c0b8bb6fd4e98a253dd2d040cff212025-08-19T22:49:34ZengWolters Kluwer Medknow PublicationsIndian Journal of Health Sciences and Biomedical Research KLEU2542-62142542-62222024-01-01171212510.4103/kleuhsj.kleuhsj_226_23Prediction of low birth weight (LBW) among smokeless tobacco-using pregnant mothers by using stepwise logistic regression modelPraveen GanganahalliSatish V KakadeJyotsna A PatilAsha PratinidhiINTRODUCTION: Children's health is tomorrow's wealth is one of the WHO's slogans of the recent years. However, children's health is to a great extent determined by factors that operate in utero, well before they are born. Newborns falling in the category of low birth weight (LBW) carry relatively greater risks of perinatal and neonatal morbidity and mortality and substandard growth and development in the later life. OBJECTIVES: The objective of the study was to study birth weight pattern of newborn babies and to find determinants of LBW among babies born to women using Mishri during pregnancy and to construct predictive model for LBW using multiple binary regression. MATERIALS AND METHODS: A cross-sectional study was conducted in the obstetric wards on women admitted for delivery and using Mishri (form of Tobacco), and they were compared with the nonusers of any form of tobacco. Details of pregnancy and delivery followed by the estimation of serum levels of cotinine using ELISA technique were collected among both groups. STATISTICAL ANALYSIS USED: Statistical analysis used multiple binary regression model and tests of significance. RESULTS: LBW is eight times more commonly seen among users of Mishri compared to nonusers of Mishri. As the cotinine level increases, there is a significant decrease in birth weight (relative risk: 4–10 times) was observed. CONCLUSIONS: Increase in cotinine levels and decrease in birth weight explain the dose–response relationship between the use of tobacco (Mishri) and adverse pregnancy outcomes (LBW). This can be applied to assess the risk among pregnant women who are using Mishri at their first antenatal care visit.http://www.ijournalhs.org/article.asp?issn=2542-6214;year=2024;volume=17;issue=1;spage=21;epage=25;aulast=Ganganahallilow birth weightmishripredictionpregnancyregression model
spellingShingle Praveen Ganganahalli
Satish V Kakade
Jyotsna A Patil
Asha Pratinidhi
Prediction of low birth weight (LBW) among smokeless tobacco-using pregnant mothers by using stepwise logistic regression model
low birth weight
mishri
prediction
pregnancy
regression model
title Prediction of low birth weight (LBW) among smokeless tobacco-using pregnant mothers by using stepwise logistic regression model
title_full Prediction of low birth weight (LBW) among smokeless tobacco-using pregnant mothers by using stepwise logistic regression model
title_fullStr Prediction of low birth weight (LBW) among smokeless tobacco-using pregnant mothers by using stepwise logistic regression model
title_full_unstemmed Prediction of low birth weight (LBW) among smokeless tobacco-using pregnant mothers by using stepwise logistic regression model
title_short Prediction of low birth weight (LBW) among smokeless tobacco-using pregnant mothers by using stepwise logistic regression model
title_sort prediction of low birth weight lbw among smokeless tobacco using pregnant mothers by using stepwise logistic regression model
topic low birth weight
mishri
prediction
pregnancy
regression model
url http://www.ijournalhs.org/article.asp?issn=2542-6214;year=2024;volume=17;issue=1;spage=21;epage=25;aulast=Ganganahalli
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AT jyotsnaapatil predictionoflowbirthweightlbwamongsmokelesstobaccousingpregnantmothersbyusingstepwiselogisticregressionmodel
AT ashapratinidhi predictionoflowbirthweightlbwamongsmokelesstobaccousingpregnantmothersbyusingstepwiselogisticregressionmodel