Ethiotime1
World | Thursday, 23 February 2023 at 12:43
Today, keeping women in the continuity of care throughout the life cycle of reproductive health such as adolescence, pregnancy, childbirth, postpartum and childhood is one of the recent global concerns. Most previous studies focus
This study aimed to describe the spatial distribution and associated factors of birth separation in the health facility after prenatal reservation in Ethiopia. In this study, the prevalence of abortion in the health institution after PC registration was 35.42%, 95% CI , and its distribution was not random. Educational status of mothers who had four or more ANC visits in Ethiopia and were counseled about pregnancy and childbirth complications, birth order, household wealth, and region were significantly associated with dropping out. The prevalence of abortion in the health facility was 35.2%, consistent with a study in Delanta, Ethiopia [32]. However, the prevalence was found to be Southern Nations Nations and Peoples Region Ethiopia 62.2% [16], Lay Gayint Region, Amhara, Northwest Ethiopia 52.7% [29] and two national studies in Ethiopia 46.52%. [33] and 55.60% [41]. Again, the finding of this study was conducted in Tanzania [42], Kenya [43], Uganda [44], Nigeria [34], Zambia. lower than one study. [45], Guinea [46] and rural Gahna [47]. The finding was lower compared to a study in 28 African countries [14] and studies in different parts of Nepal ranging from 39% to 58% [12, 13, 48]. A possible reason for this difference may be that the first three studies in Ethiopia were conducted with smaller sample sizes, and temporal variability may be due to the difference. Additionally, context differences in African countries and other developing countries can be attributed to the difference. Conversely, the prevalence of abortion in the health facility was higher compared with a study in West Gojjam [49]. It was also higher compared to a study conducted in Arbaminch, Ethiopia [50]. It was higher compared to a study conducted in India [51] and Cambodia [8]. The likely reason could be and can be attributed to context differences in African countries and other developing countries. Significant clustering was found in the eastern parts of the SNNP, Central and Southwest Amhara, northern, southern and western Afar, eastern Somalia, and the Harari region, and outliers were found in Dire Dewa, eastern Harari, Assosa, northern Shewa, Dawuro Welayta. Gamo-Goffa, Wollo north and south, Gondar north and south. Hotspot areas were found in southern and northern Gondar, Central Afar, northern and southern Wollo, Hadia, Sidama and Geddio regions, and cold spot areas include blue colored dots/clusters found in Dire Dawa, Harari, South West and East. Shewa and Assosa. The primary cluster included almost all parts of the Somali region and parts of Harari and Oromia. However, secondary clusters include: all parts of Tigray and Afar regions, large parts of Amhara region, parts of Oromia and SNNP regions. In the spatial kriging interpolation analysis, Northern and Eastern parts of Somalia and SNNP region, Southern part of Oromia region and majority of Afar predicted a high probability of dropping out of school compared to other regions. However, the two administrative cities and the surrounding areas were predicted to be less likely to drop out. While the government strives to achieve the SDG, a significant number of women are leaving healthcare facility delivery. If the problem persists or worsens, the expected reduction in maternal and child morbidity and mortality will not be achieved. Therefore, healthcare providers, policy makers, and programmers should invest their resources in women, even after ANC reservation. The result of this study showed that the probability of dropping out of healthcare facility delivery after antenatal reservation was negatively associated with educational status. The result is in line with studies in different parts of Ethiopia [15, 16, 52]. It is also similar to studies conducted in a multi-country study in 49 and 28 countries, including Africa [5, 14]. The conclusion was also supported by a study conducted in Nepal [48]. Studies in Pakistan and Cambodia have shown the same finding [8, 53]. The possible rationale for the association may be that educated women can easily understand the possible complications of pregnancy and childbirth. Conversely, untrained women may perceive skilled obstetricians and delivery in a health facility as necessary for women experiencing obstetric complications [54]. The result of this study showed that mothers with higher birth order were more likely to leave the birth in the health facility than first order mothers. This is in line with a national-level study conducted in Ethiopia [33]. It is also similar to a study done in Nigeria [34] and Cambodia [8]. However, the result is in contrast to a study done in Tanzania [42]. The possible reason for this difference may be the difference in the context and values of the children. The connotation may be due to insufficient satisfaction with previous services or a negative attitude from one’s or others’ experiences. Also, their first order of birth has not experienced birth and may be afraid of dying [55]. Women with four or more ANC visits were less likely to drop out than those with fewer than four ANC visits. The finding is similar to a study conducted in the Southern Nation and Peoples Region in Ethiopia [16]. Studies in Cambodia and 28 African countries have shown the same evidence [8, 14]. However, it is inconsistent in a Tanzanian study [42]. The possible reason for this relationship may be that the frequent contact between the mother and the health care provider builds trust and confidence. Women who were counseled about pregnancy and childbirth complications were less likely to drop out than those who did not receive counseling. The finding is similar to studies conducted in different parts of Ethiopia [15, 33]. However, this is in contrast to a study conducted in 28 African countries [14]. The possible difference for this may be the difference in counseling methods and experiences. The possible reason for the association may be that every pregnant woman can clearly understand during the counseling that she is at risk. The final model showed that the probability of abortion at the health facility was negatively related to the wealth of mothers/households. The result is similar to a national-level study conducted in Ethiopia [52]. It is also consistent with a study done in Guinea [34]. Other studies conducted in 49 different countries, including Pakistan, India, and African countries, showed the same finding [5, 51, 53]. The probable reason for attribution is that the higher the wealth, the more they don’t worry about the expense during shipping and/or after delivery. Mothers living in Afar and Oromia were more likely to discontinue labor in the health facility compared to Tigray. This study is similar to a study done in Ethiopia [52]. The possible reason for the association may be that some parts of the above-mentioned regions are shepherds and have difficulty staying in a settlement for a long time. This study was conducted using multilevel logistic regression analysis, which can identify multilevel factors at different levels, which will provide important information for designing interventions. The results are representative of the entire Ethiopian population due to appropriate estimation adjustments such as weighting. Also, the spatial analysis showed the hottest spot areas. Despite its power, the current study’s findings have limitations. Due to the cross-sectional nature of the study design, the ability of this article to establish a causal relationship among those associated is limited. Due to the use of secondary data, important variables such as intranatal and postnatal cultural beliefs, partner factors and danger signs information were not included in the data set, so these variables were not included in the analysis. Gotopnews.com
Keywords
#Ethiopia #Health #SpatialDistribution #WomenS #AntenatalBooking #AssociatedFactors #DropoutHealth #FacilityDelivery #MultilevelAnalysis
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