Essential newborn care practice and its associated factors in Southwest Ethiopia

Machine learning applied in maternal and fetal health: a narrative review focused on pregnancy diseases and complications

Introduction

Machine learning (ML) corresponds to a wide variety of methods that use mathematics, statistics and computational science to learn from multiple variables simultaneously. By means of pattern recognition, ML methods are able to find hidden correlations and accomplish accurate predictions regarding different conditions. ML has been successfully used to solve varied problems in different areas of science, such as psychology, economics, biology and chemistry. Therefore, we wondered how far it has penetrated into the field of obstetrics and gynecology.

Aim

To describe the state of art regarding the use of ML in the context of pregnancy diseases and complications.

Methodology

Publications were searched in PubMed, Web of Science and Google Scholar. Seven subjects of interest were considered: gestational diabetes mellitus, preeclampsia, perinatal death, spontaneous abortion, preterm birth, cesarean section, and fetal malformations.

Current state

ML has been widely applied in all the included subjects. Its uses are varied, the most common being the prediction of perinatal disorders. Other ML applications include (but are not restricted to) biomarker discovery, risk estimation, correlation assessment, pharmacological treatment prediction, drug screening, data acquisition and data extraction. Most of the reviewed articles were published in the last five years. The most employed ML methods in the field are non-linear. Except for logistic regression, linear methods are rarely used.

Future challenges

To improve data recording, storage and update in medical and research settings from different realities. To develop more accurate and understandable ML models using data from cutting-edge instruments. To carry out validation and impact analysis studies of currently existing high-accuracy ML models.

Conclusion

The use of ML in pregnancy diseases and complications is quite recent, and has increased over the last few years. The applications are varied and point not only to the diagnosis, but also to the management, treatment, and pathophysiological understanding of perinatal alterations. Facing the challenges that come with working with different types of data, the handling of increasingly large amounts of information, the development of emerging technologies, and the need of translational studies, it is expected that the use of ML continue growing in the field of obstetrics and gynecology.

Spatial distribution and determinants of newborn care within 2 days of postpartum period among women with at least one antenatal care visit in Ethiopia: Mixed effect multilevel analysis

INTRODUCTION

Neonatal mortality is pervasive in developing countries like Ethiopia. Though the risk of neonatal mortality is preventable through consolidating simple, low-cost, and less time-consuming essential care, there is a scarcity of evidence about the spatial distribution of newborn care in Ethiopia.

OBJECTIVE

The current study aimed to demonstrate spatial distribution and determinants of newborn care within 2 days of the postpartum period in Ethiopia.

METHODS

A cross-sectional study was employed based on Ethiopian demographic and health survey 2016 data and 2796 post-partum period women were included. Arc GIS version 10.7 and SaTScan version 9.6 software were used. Mixed effect analysis was done by STATA version 14 software. Bivariate analysis was done and variables with a p value<0.2 were taken as a candidate for multilevel multivariable logistic regression. Intra Class Correlation Coefficient (ICC), Proportion Change in Variance (PCV), and Median Odds Ratio (MOR) were used for model comparison and an Adjusted Odds Ratio (AOR) with respect to a 95% confidence interval was used for declaring statistical significance. In the multivariable analysis, a p-value≤0.05 was considered as a cut point of statistical significance with the outcome variable.

RESULTS

The spatial distribution of newborn care was not random and the overall prevalence was 48.39%. Secondary educational level (Adjusted Odds Ratio (AOR = 1.5;95% CI 1.06,2.62), college and above (AOR = 2.47; 95% CI 1.22,5.01), number of antenatal cares three (AOR = 1.5; 95% CI 1.10, 2.04), antenatal care four and above (AOR = 1.6; 95% CI 1.22; 2.19), place of delivery (AOR = 9.67; 7.44, 12.57) and child is a twin (AOR = 3.33; 95% CI 1.23, 9.00) were variables significantly associated with newborn care.

CONCLUSIONS

Newborn care practice in Ethiopia is below half per hundred participants. Even the distribution was not random. There is a need to pay attention to those cold spot areas and factors significantly associated with newborn care. Improving women's educational levels secondary and above, and consolidating the continuation of antenatal care and health facility delivery were the priority areas to improve newborn care in Ethiopia. Maternal and neonatal health program managers and policymakers should pay attention to those cold spots of newborn care to achieve the sustainable development goal.

Early Baby Bathing Practice and its Associated Factors Among Mothers who Give Birth in the Past One Month in Gurage Zone, Ethiopia, 2022

Background

Ethiopia has still suffered the highest burden of neonatal morbidity and mortality. The World Health Organization's practical guide for the thermal protection of newborns recommends delaying the bathing of newborns for at least 24 h following delivery, as it is crucial to prevent neonatal mortality and morbidity and to achieve 2030 sustainable development goals. However, little is known about delayed newborn bathing practices in Ethiopia. Therefore, the purpose of this study was to assess early baby bathing practices and associated factors among postpartum women.

Methods

A mixed community-based cross-sectional study was conducted among a total of 582 postnatal mothers. A multistage sampling technique was used to select study participants. A pre-tested and structured questionnaire was used to collect data. The data was entered into Epi-Data version 4.2.0 and exported into SPSS version 23 for analysis. Three focus group discussions with postnatal mothers were used for qualitative data. A purposive sampling method was used. Thematic analysis was used for qualitative data. Bivariate and multivariate logistic regression analyses were used in the analysis. To declare statistically significant, p-values of .05 were used.

Result

This study revealed that 250 (43%) mothers were practicing early newborn bathing. Early baby bathing was associated with antenatal care (ANC) follow-up (AOR  =  5.1  =  .95% CI  =  (2.6-9.9)), having no recent complications during birth (AOR  =  1.9  =  95% CI  =  (1.02-3.6), having information about the time of baby bathing (AOR  =  6.02, 95% CI  =  (3.9, 9.3)), knowledge of hypothermia (AOR  =  3.3  =  95.6% CI (1.9-5.8), and poor knowledge about neonatal danger signs.

Conclusion and Recommendation

ANC follow-up, recent complications during birth, having information, knowledge about hypothermia, and neonatal danger signs were significantly associated with early baby bathing. Continuous health education on the appropriate time of baby bathing and neonatal danger signs and enhanced ANC service utilization are recommended.

Knowledge and practice of essential newborn care and associated factors among women in Ethiopia: systematic review and meta-analysis

Background

In developing countries, including Ethiopia the risk of neonatal death can be easily prevented and avoided by implementing essential newborn care with simple, low cost, and a short period time immediately after delivery. However, the problem is still persisting due to lack of adequate maternal and newborn care practice. Hence, this review aimed to estimate the pooled prevalence of women’s knowledge and practice of essential newborn care and its associated factors in Ethiopia using systematic review and meta-analysis.

Method

An intensive literature search was performed from PubMed, Google Scholar, EMBASE, HINARI, Scopus, and Web of Sciences from April 1–30, 2021. Data were extracted by using a pre-tested and standardized data extraction format. The data were analyzed by using STATA 14 statistical software. I² tests assessed heterogeneity across the included studies. A random-effect model was used to estimate the pooled prevalence of knowledge and practice of essential newborn care.

Results

From 1275 identified studies, 25 articles were included. The national pooled prevalence of essential newborn care knowledge and practice among women was 55.05% and 41.49% respectively. Secondary education (AOR = 2.75, 95% CI 1.62, 4.66), multiparity (AOR = 2.14, 95% CI 1.41, 3.26), antenatal care (AOR = 2.94; 95% CI 2.03, 4.26), and postnatal follow-up (AOR = 1.64, 95% CI 1.20, 2.23) were significantly associated with knowledge level whereas; primary education (AOR = 7.08, 95% CI 4.79, 10.47), urban residency (AOR = 2.22, 95% CI 1.65, 3.00), attending monthly meetings (AOR = 2.07, 95% CI 1.64, 2.62), antenatal care (AOR = 2.89, 95% CI 1.97, 4.26), advised during delivery (AOR = 2.54, 95% CI 1.80, 3.59), postnatal follow-up (AOR = 7.08, 95% CI 4.79, 10.47) and knowledge (AOR = 2.93; 95% CI 1.81, 4.75) were statistically significant with essential newborn practice.

Conclusions

The current systematic review and meta-analysis findings reported that the level of knowledge and practice of essential newborn care among Ethiopian women was low. Therefore, improvement of essential newborn through the provision of community-based awareness creation forum, improving antenatal and postnatal care follow up, education on essential newborn care to all pregnant and postnatal women are very important.

Trial registration Prospero registration: CRD 42021251521

Supplementary Information

The online version contains supplementary material available at 10.1186/s12978-022-01480-0.

Essential newborn care (ENC) is a single most cost-effective intervention to reduce neonatal mortality and morbidity both in developed and developing countries. An intensive electronic search from PubMed, Google Scholar, EMBASE, HINAR, Scopus, and Web of Sciences were performed to identify the primary studies. In this meta-analysis a total of 25 articles were included to estimate the polled prevalence of ENC knowledge and practice among Ethiopian women. Accordingly, the national pooled prevalence of ENC knowledge and practice among women was 55.05% and 41.49% respectively. In the current systematic review and meta-analysis, Secondary education, multiparity, antenatal care, and postnatal follow-up were significantly associated with knowledge level whereas; primary education, urban residency, attending monthly meetings, antenatal care, advised during delivery, postnatal follow-up and knowledge on ENC were found to be statistically significant with essential newborn practice. As per finding the knowledge and practice regarding essential newborn care among women in Ethiopian was significantly low. Hence, improvement of essential newborn through the provision of community-based awareness creation forum, improving antenatal and postnatal care follow up, education on essential newborn care to all pregnant and postnatal women are very important.