Maternal Factors and Utilization of the Antenatal Care Services during Pregnancy Associated with Low Birth Weight in Rural Nepal: Analyses of the Antenatal Care and Birth Weight Records of the MATRI-SUMAN Trial

Acharya, Dilaram; Singh, Jitendra Kumar; Kadel, Rajendra; Yoo, Seok-Ju; Park, Ji-Hyuk; Lee, Kwan

doi:10.3390/ijerph15112450

Cited by 45 publications

(61 citation statements)

References 54 publications

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“…Mothers involved in labor work were five times and mothers who were unemployed or housewives were two times more likely to deliver LBW baby than the employed counterpart. is finding aligns with the study conducted in Lithuania, Vientiane, and Nepal [22][23][24] which revealed that mother's employment status is significantly associated with LBW. e role of education and employment on infant birth weight might be due to various interactions among social determinants of health.…”

Section: Discussionsupporting

confidence: 91%

Predictors of Low Birth Weight at Lumbini Provincial Hospital, Nepal: A Hospital-Based Unmatched Case Control Study

Shrestha

Shrestha²,

Gyawali

2020

Advances in Preventive Medicine

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Background. Low birth weight (LBW) is defined as the birth weight of live born infants below 2500 g, regardless of gestational age. It is a public health problem caused by factors that are potentially modifiable. The purpose of this study was to determine the socioeconomic, obstetric, and maternal factors associated with LBW in Lumbini Provincial Hospital, Nepal. Methods. The study was conducted using case control study design with 1 : 2 case control ratio. A total of 105 cases and 210 controls were taken in this study. Data were entered on Epi data software version 3.1 and exported to Statistical Package for Social Science (SPSS) software version 25 for analysis. Characteristics of the sample were described using mean and standard deviation. Bivariate analysis was done to assess the association between dependent and independent variables. The ultimate measure of association was odds ratio. Variables found to be associated with bivariate analysis were entered into a multivariable logistic regression model to identify predictors of LBW. Results. The mean age of the participants was 25.98 years with ±4.40 standard deviation. Mothers with literate educational background (AOR 0.32, 95% CI 0.13–0.81), housewife (AOR 2.63, 95% CI 1.11–6.20), vaginal mode of delivery (AOR 0.45, 95% CI 0.25–0.82), gestational age <37 weeks (AOR 2.51, 95% CI 1.15–5.48), history of LBW (AOR 5.12, 95% CI 1.93–13.60), and maternal weight <50 kilograms (AOR 2.23, 95% CI 1.23–4.02) were significantly associated with LBW. Conclusion. Educational and occupational status, mode of delivery, gestational age, maternal weight, and history of LBW were found to be independent predictors of LBW. There is need of developing coordination with education sector for increasing educational status of mothers and adolescent girls. Social determinants of health need to be considered while developing interventional programs. Similarly, interventional programs need to be developed considering identified predictors of low birth weight.

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Section: Discussionsupporting

confidence: 91%

Predictors of Low Birth Weight at Lumbini Provincial Hospital, Nepal: A Hospital-Based Unmatched Case Control Study

Shrestha

Shrestha²,

Gyawali

2020

Advances in Preventive Medicine

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“…The mothers who deliver female babies had higher odds of bearing low birth weight neonate as compared to those who deliver male neonates. This result is in line with the findings in Ghana (44) and Nepal (45). The association could be explained by the pathophysiologic mechanism in the uterus.…”

Section: Discussionsupporting

confidence: 92%

Spatial distribution and factors associated with low birth weight in Ethiopia using data from Ethiopian demographic and health survey 2016: spatial and multilevel analysis

Liyew

Sisay

Muche

2020

Preprint

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Background: Low birth weight (LBW) was a leading cause of neonatal mortality. It showed an increasing trend in Sub-Saharan Africa for the last one and half decade. Moreover, it was a public health problem in Ethiopia. Even though different studies were conducted to identify its predictors, contextual factors were insufficiently addressed in Ethiopia. There was also limited evidence on the spatial distribution of low birth weight. Therefore, this study aimed to explore spatial distribution and factors associated with low birth weight in Ethiopia.Method: Secondary data analysis was conducted using the 2016 EDHS data. A total of 1502 (weighted sample) mothers whose neonates were weighed at birth five years preceding the survey were included. GIS 10.1, SaTscan, stata, and Excel were used for data cleaning and analysis. A multi-level mixed-effects logistic regression model was fitted to identify factors associated with low birth weight. Finally, hotspot areas from GIS results, log-likelihood ratio (LLR) and relative risk with p-value of spatial scan statistics, AOR with 95% CI and random effects for mixed-effects logistic regression model were reported.

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“…Thus, female neonates had higher odds of being low birth weight babies as compared to male neonates. This result is in line with the ndings in Ghana (40) and Nepal (41). The association could be explained by the pathophysiologic mechanism in the uterus.…”

Section: Discussionsupporting

confidence: 91%

Spatial Distribution and Factors Associated with Low birth weight in Ethiopia using data from Ethiopian Demographic and Health Survey 2016; Spatial and Multilevel analysis

Liyew

Sisay

Muche

2020

Preprint

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Background Low birth weight (LBW) is a leading cause of neonatal mortality. In Ethiopia, it is a public health problem that contributes to the majority of newborn deaths. To date, the effect of contextual factors on LBW was largely overlooked in Ethiopia. Besides, there is also limited evidence on the geographic variation of low birth weight in Ethiopia. Therefore, this study aimed to explore spatial distribution as well as individual and community-level factors associated with low birth weight in Ethiopia. Method: Secondary data analysis was conducted using the 2016 Ethiopian Demographic and Health Survey (EDHS) data. A total of 1502 neonates were included in this study. Spatial autocorrelation analysis was conducted to assess the spatial dependency of LBW. Besides, the spatial scan statistics and ordinary kriging interpolation were done to detect the local level clusters and to assess predicted risk areas respectively. Furthermore, a multi-level logistic regression model was fitted to determine individual and community-level factors associated with low birth weight. Finally, most likely clusters with log-likelihood ratio (LLR), relative risk and p-value from spatial scan statistics, and AOR with 95% CI for multi-level logistic regression model were reported. Results Low birth weight was spatially clustered in Ethiopia. Primary (LLR = 11.57; P = 0.002) clusters were detected in the Amhara region. It showed that neonates within the spatial window had 2.66 times higher risk of being LBW baby as compared to those outside the window. Besides, secondary (LLR = 11.4; P = 0.003;LLR = 10.14,P = 0.0075) clusters were identified at Southwest Oromia, north Oromia, south Afar, and Southeast Amhara regions. Neonates who were born from severely anemic (AOR = 1.47;95%CI 1.04,2.01), and uneducated (AOR = 1.82;95%CI1.12,2.96) mothers, as well as those who were born before 37 weeks of gestation (AOR = 5.91;95%CI3.21,10.10) and females (AOR = 1.38;95%CI1.04,1.84), had significantly higher odds of being low birth weight babies. Conclusion The high-risk areas of low birth weight were detected in Afar, Amhara, and Oromia regions. Therefore, targeting the policy interventions in those risk areas by focusing on the improvement of maternal education, strengthening anemia control programs and elimination of modifiable causes of prematurity could be vital for reduce the low birth weight disparity in Ethiopia.

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Maternal Factors and Utilization of the Antenatal Care Services during Pregnancy Associated with Low Birth Weight in Rural Nepal: Analyses of the Antenatal Care and Birth Weight Records of the MATRI-SUMAN Trial

Cited by 45 publications

References 54 publications

Predictors of Low Birth Weight at Lumbini Provincial Hospital, Nepal: A Hospital-Based Unmatched Case Control Study

Predictors of Low Birth Weight at Lumbini Provincial Hospital, Nepal: A Hospital-Based Unmatched Case Control Study

Spatial distribution and factors associated with low birth weight in Ethiopia using data from Ethiopian demographic and health survey 2016: spatial and multilevel analysis

Spatial Distribution and Factors Associated with Low birth weight in Ethiopia using data from Ethiopian Demographic and Health Survey 2016; Spatial and Multilevel analysis

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