Magnitude of Anemia and Its Associated Factors among Pregnant Women Attending Antenatal Care at Najo General Hospital, Northwest Ethiopia

Gari, Wakshuma; Tsegaye, Arega; Ketema, Tsige

doi:10.1155/2020/8851997

Cited by 13 publications

(13 citation statements)

References 20 publications

(24 reference statements)

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“…The current results both showed that most respondents have at-risk parity and indicated that parity does not significantly affect anemia in pregnant women, as the proportion of anemia among pregnant women with at-risk and no-risk parity was the same. This is in line with research conducted by Gari, Tsegaye, & Ketema (2020), which showed that parity did not have a significant association with anemia.…”

Section: Paritysupporting

confidence: 92%

Determinants of Anemia in The Third Trimester of Pregnancy in Mojokerto

Irawati

Syalfina

Priyanti

et al. 2021

JBE

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Background: Anemia is a pregnancy complication that increases the morbidity and mortality of mother and baby during pregnancy and until puerperium. In 2015, the incidence of anemia in Indonesia was 23%. Purpose: The aim of this study was to determine factors that influence anemia in the third trimester of pregnancy. Methods: The study was conducted on pregnant women in Mojokerto. This study used a case-control design. The sample calculation results obtained 70 cases and 70 controls. The primary and secondary data were obtained from the MCH book and from interviews conducted according to questionnaire guidelines. Data were analyzed via chi-squared test and logistic regression test. Results: The factors that influence anemia in the third trimester of pregnancy were found to be age (p value = 0.04; OR 2.08; 95% CI = 1.04–4.16), occupation (p value = 0.02; OR = 2.27; 95% CI = 1.15–4.47), birth interval (p value = 0.03; OR = 2.25; 95% CI 1.08-4.69), nutritional status (p value = 0.02; OR = 2.33; 95% CI = 1.14- 4.82), knowledge [about anemia] (p value = 0.01; OR = 3.17; 95% CI = 1.41-7.09), income per month (p value = 0.03, OR = 2.25; 95% CI =1.08–4.69), smoking activity (p value = 0.04; OR = 2.00; 95% CI = 1.02–3.92), perception (p value = 0.02; OR = 2.20; 95% CI = 1.10–4.40) , and spousal support (p value = 0.01; OR = 2.63; 95% CI = 1.16 – 5.93) Conclusion: The most influential factors on anemia in the third trimester of pregnancy were birth interval, nutritional status, and knowledge.

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Section: Paritysupporting

confidence: 92%

Determinants of Anemia in The Third Trimester of Pregnancy in Mojokerto

Irawati

Syalfina

Priyanti

et al. 2021

JBE

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“…The possible explanation for anaemia related death during the postpartum period relates to women's circulatory decomposition, which is manifested by increased cardiac output and decreased ability to blood loss, which ultimately results in shock and death [97]. On the other hand, the risk factors of anaemia such as low dietary intake of iron, intestinal or blood parasite infection, and chorine illness [98,99], could be handled during ANC visit by supplementation of iron, folic acid, and deworming.…”

Section: Discussionmentioning

confidence: 99%

Critical factors associated with postpartum maternal death in Ethiopia

et al. 2022

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Background Globally most maternal deaths occur during the postpartum period; however, the burden is disproportionately higher in some Sub-Saharan African countries including Ethiopia. According to Ethiopian Ministry of Health’s annual report, in 2019 alone, nearly 70% of maternal deaths happen during the postpartum period. Although several studies have been conducted on postpartum maternal deaths in Ethiopia, most of the studies were focused either on individual-level or district-level determinants with limited emphasis on the timing of death and in relatively small and localized areas. Therefore, this study aimed at identifying the determinants of postpartum death both at an individual and districts level, which could shed light on designing pragmatic policies to reduce postpartum maternal death. Methods The study utilized secondary data obtained from the Ethiopian maternal death surveillance system. A total of 4316 reviewed maternal death from 645 districts of Ethiopia were included in the analysis. A multilevel multinomial logistic regression model was applied to examine factors significantly associated with postpartum maternal death in Ethiopia. Result The findings revealed that 65.1% of maternal deaths occurred during the postpartum period. The factors associated with postpartum death included previous medical history (history of ANC follow up and party), medical causes (obstetrics haemorrhage, hypertensive disorder of pregnancy, pregnancy-related infection, and non-obstetrics complication), personal factors (poor knowledge of obstetrics complication), and facility-level barriers (shortage of life-saving maternal commodities and delay in receiving treatment). Conclusion Almost seven in ten maternal deaths happen during the postpartum period. The rate was even higher for some women based on their previous medical history, level of awareness about obstetrics complication, medical conditions, as well as the readiness of the health facility at which the women was served. Since the postpartum period is identified as a critical time for reducing maternal death, policies and actions must be directed towards improving health education, ANC service utilization, and facility-level readiness.

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“…Anemia in pregnant women can be caused by parasitic infestation, socio-demographic status, economic status, dietary practice, obstetric factors, reproductive health, and other health-related factors [ 5 ]. More than 115,000 maternal deaths and 591,000 prenatal deaths are caused by anemia disease in the world per year [ 6 ]. According to the World Health Organization (WHO, 1993–2005) report, anemia affects 41.8% of pregnant women worldwide, with Africa having the highest prevalence (57.1%) [ 7 , 8 ].…”

Section: Introductionmentioning

confidence: 99%

“…Most of the women who live in the rural areas of Ethiopia have been affected by this disease due to different factors including nutrition, parasites, socio-demographic, obstetric, reproductive characteristics, and the like [ 10 ]. According to WHO guidelines, the minimum acceptable hemoglobin level during pregnancy is 11 g/dl, during the first half, 10.5 g/dl, during the second half, and 12 g/dl for lactating women [ 6 , 10 , 11 ]. To understand and predict the level of anemia among pregnant women in the case of Ethiopia, several types of research have been conducted.…”

Section: Introductionmentioning

confidence: 99%

“…To understand and predict the level of anemia among pregnant women in the case of Ethiopia, several types of research have been conducted. For example, [ 3 , 6 – 14 ] investigated the status of anemia among pregnant women using cross-sectional statistical methods. They also used bivariate and multivariate logistic regression methods and identified the most determinant risk factors.…”

Section: Introductionmentioning

confidence: 99%

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Predicting the level of anemia among Ethiopian pregnant women using homogeneous ensemble machine learning algorithm

Dejene

Abuhay

Bogale

2022

BMC Med Inform Decis Mak

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Background More than 115,000 maternal deaths and 591,000 prenatal deaths occurred in the world per year with anemia, the reduction of red blood cells or hemoglobin in the blood. The world health organization divides anemia in pregnancy into mild anemia (Hb 10–10.9 g/dl), moderate anemia (Hb 7.0–9.9 g/dl), and severe anemia (Hb < 7 g/dl). This study aims to predict the level of anemia among pregnant women in the case of Ethiopia using homogeneous ensemble machine learning algorithms. Methods This study was conducted following a design science approach. The data were gathered from the Ethiopian demographic health survey and preprocessed to get quality data that are suitable for the machine learning algorithm to develop a model that predicts the levels of anemia among pregnant. Decision tree, random forest, cat boost, and extreme gradient boosting with class decomposition (one versus one and one versus rest) and without class decomposition were employed to build the predictive model. For constructing the proposed model, twelve experiments were conducted with a total of 29,104 instances with 23 features, and a training and testing dataset split ratio of 80/20. Results The overall accuracy of random forest, extreme gradient boosting, and cat boost without class decompositions is 91.34%, 94.26%, and 97.08.90%, respectively. The overall accuracy of random forest, extreme gradient boosting, and cat boost with one versus one is 94.4%, 95.21%, and 97.44%, respectively. The overall accuracy of random forest, extreme gradient boosting, and cat boost with one versus the rest are 94.4%, 94.54%, and 97.6%, respectively. Conclusion Finally, the researcher decided to use cat boost algorithms with one versus the rest for further use in the development of artifacts, model deployment, risk factor analysis, and generating rules because it has registered better performance with 97.6% accuracy. The most determinant risk factors of anemia among pregnant women were identified using feature importance. Some of them are the duration of the current pregnancy, age, source of drinking water, respondent’s (pregnant women) occupation, number of household members, wealth index, husband/partner's education level, and birth history.

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Magnitude of Anemia and Its Associated Factors among Pregnant Women Attending Antenatal Care at Najo General Hospital, Northwest Ethiopia

Cited by 13 publications

References 20 publications

Determinants of Anemia in The Third Trimester of Pregnancy in Mojokerto

Determinants of Anemia in The Third Trimester of Pregnancy in Mojokerto

Critical factors associated with postpartum maternal death in Ethiopia

Predicting the level of anemia among Ethiopian pregnant women using homogeneous ensemble machine learning algorithm

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