Introduction Neural tube defects affect the brain and the spinal cord of the developing embryo. The defects occur due to incomplete or failure of closure of the neural tube. The condition eventually causes death and lifelong disability. Worldwide, more than 300,000 babies are born with neural tube defects each year. The highest burden is in low- and middle-income countries. Therefore, this study aims to identify the risk factors associated with neural tube defects among mothers who gave birth in North Shoa Zone Hospitals. Methods A hospital based unmatched case-control study was conducted among 243 (81 cases and 162 controls) study participants in North Shoa Zone Hospitals. The hospitals were selected using simple random sampling and all cases and randomly selected controls in the selected hospitals were included in the study. The data were collected by using pre-tested structured questionnaire. Results Different factors were identified to have association with neural tube defect. Family annual cash income less than 24000ETB (AOR: 3.73, 95%CI: 1.35, 10.26), history of still birth (AOR: 3.63, 95%CI: 1.03, 12.2), history of abortion (AOR: 6.15, 95%CI: 2.63, 18.56), preconception tea use (AOR: 2.36, 95%CI: 1.15, 4.86) and pesticides/chemical exposure (AOR: 5.34, 95%CI: 1.77, 16.05) were positively associated factors. In contrast, preconception care (AOR: 0.14, 95%CI: 0.05, 0.39) and taking iron/folic acid/multivitamin during the current pregnancy (AOR: 0.16, 95%CI: 0.07, 0.33) showed a protective effect. Conclusion Family annual income less than 24000ETB, history of still birth, history of abortion, preconception tea uses and pesticides/chemical exposure were associated factors of neural tube defects. Preconception counseling and screening should be recommended for women who plan for pregnancy.
BackgroundA maternal near-miss (MNM) refers to a woman who presents with life-threatening complications during pregnancy, childbirth, or within 42 days of termination of pregnancy but survived by chance or due to the standard care she received. It is recognized as a valuable indicator to examine the quality of obstetrics care as it follows similar predictors with maternal death. Ethiopia is one of the sub-Saharan African countries with the highest rate of maternal mortality and morbidity. Thus, studying the cause and predictors of maternal near-miss is vital to improving the quality of obstetric care, particularly in low-income countries.ObjectiveTo identify determinants of maternal near-miss among women admitted to public hospitals in North Shewa Zone, Ethiopia, 2020.MethodsA facility-based unmatched case-control study was conducted on 264 women (88 cases and 176 controls) from February to April 2020. Data were collected using pretested interviewer-administered questionnaires and a review of medical records. Data were entered into Epi-data version 4.2.2 and exported to SPSS version 25 for analysis. Variables with a p-value <0.25 in the bivariable analysis were further analyzed using multivariable logistic regression analysis. Finally, variables with a p-value <0.05 were considered statistically significant.ResultSevere pre-eclampsia (49.5%) and postpartum hemorrhage (28.3%) were the main reasons for admission of cases. Educational level of women (AOR = 4.80, 95% CI: 1.78–12.90), education level of husbands (AOR = 5.26; 95% CI: 1.46–18.90), being referred from other health facilities (AOR = 4.73, 95% CI: 1.78–12.55), antenatal care visit (AOR = 2.75, 95% CI: 1.13–6.72), cesarean section (AOR = 3.70, 95% CI: 1.42-9.60), and medical disorder during pregnancy (AOR = 12.06, 95% CI: 2.82–51.55) were found to significantly increase the risk of maternal near-miss. Whereas, the younger age of women significantly decreased the risk of maternal near miss (AOR = 0.26, 95% CI: 0.09–0.75).ConclusionAge, educational level, antenatal care follow-ups, medical disorder during pregnancy, mode of admission, and mode of delivery were significant predictors of maternal near-miss. Socio-demographic development, use of ANC services, early detection and management of medical diseases, reducing cesarean section, and improving the referral systems are crucial to minimizing the maternal near-miss.
Background Optimizing women’s health and knowledge of preconception healthcare before conceiving a pregnancy decreases the risk of adverse pregnancy outcomes. However, preconception health care is one of the missing pillars in the continuum of maternal and child health care in Ethiopia. Therefore, this study aimed to assess knowledge of pre-conception health, its relation to planned pregnancy, parity, family planning use, and education among married women in Southern Ethiopia. Methods A community-based cross-sectional study was conducted with 337 married women recruited from March 25 to April 30, 2018 in Jinka town. A simple random sampling technique was employed and the data was collected using a structured questionnaire. Data analysis involved calculating frequencies, percentages, and logistic regression. Associations were assessed using odds ratios and 95% confidence intervals with statistical significance determined at a p-value < 0.05. Results The overall women’s preconception health care knowledge score in this study was 55.2%, which is a moderate score. In multivariable analyses, women’s secondary level of education [AOR = 2.3; 95% CI = 1.13–4.87], family planning use [AOR = 2.6, 95% CI = 1.37–4.87], planned pregnancy [AOR = 3.2, 95% CI = 1.35–7.44], Nullyparity [AOR = 21.2; 95% CI = 4.92–91.5], and market trade vendors [AOR = 2.5; 95%CI = 1.06–6.03], were significantly associated with knowledge of preconception health care. Conclusion The findings show that women’s knowledge of preconception health care is moderate. Women’s knowledge of preconception health care can be linked to their level of education, use of family planning methods, pregnancy planning, and Nullyparity. Therefore, the government and other key stakeholders need to develop a specific education package that improves women’s knowledge of preconception care and pregnancy planning, taking into account factors such as levels of education and literacy when designing implementation strategies.
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