| Literature DB >> 35093008 |
Sitota Tsegaye1, Kalkidan Yibeltal2, Haset Zelealem3, Walelegn Worku4, Meaza Demissie5, Alemayehu Worku6,7, Yemane Berhane7.
Abstract
BACKGROUND: Antenatal care is an essential platform to provide all the necessary health interventions during pregnancy that aim to reduce maternal and newborn morbidity and mortality. Although the antenatal care coverage has been increasing in Ethiopia in the last two decades, the country has not been able to meet its own coverage target to date. Most pregnant women who initiated antenatal care also do not complete the full recommended follow up contacts. This study investigated the trend in coverage and the inequalities related to the use of antenatal care in Ethiopia.Entities:
Keywords: Antenatal care; Ethiopia; Household wealth; Inequality; Maternal education; Residence
Mesh:
Year: 2022 PMID: 35093008 PMCID: PMC8801127 DOI: 10.1186/s12884-021-04326-y
Source DB: PubMed Journal: BMC Pregnancy Childbirth ISSN: 1471-2393 Impact factor: 3.007
Fig. 1National Trend for at least one and 4 or more Antenatal Care visits Coverage trend 2000-2019 and projections for 2025 based on smoothed average for Ethiopia
Fig. 2Antenatal care coverage inequality among wealth groups in Ethiopia, 2000-2019 a Coverage gaps between wealth strata; b Concentration curve and c Relative concentration index by household wealth quintile (2000-2016)
Fig. 3Antenatal care coverage inequality among education groups in Ethiopia, 4,242,000-2019 a Coverage gaps; b Concentration curve and c Relative concentration index by maternal education status (2000-2016)
Fig. 4Antenatal care coverage inequality by residence area (rural Vs urban) in Ethiopia, 2000-2019 a Coverage gaps; b Ratio by place of residence (2000-2016)
Logit decomposition of the four or more ANC visits service utilization inequality by area of resident. (Ethiopia, 2016)
| Age | .002767 | .0010237 | 2.70 | 0.007 | .00076063, .0047734 | −.71782 |
| Economic status | −.24693 | .03045 | − 8.11 | 0.000 | −.30661, −.18725 | 64.058 |
| Highest educational level | −.10979 | .011865 | − 9.25 | 0.000 | −.13305, −.086536 | 28.482 |
| Occupation | −.0002908 | .0014452 | − 0.20 | 0.841 | −.0031234, .0025418 | .07544 |
| Mass media | −.0001329 | .0030584 | − 0.04 | 0.965 | −.0061273, .0058615 | .034477 |
| Marital status | .00011897 | .0017303 | 0.07 | 0.945 | −.0032723, .0035103 | −.030863 |
| Age | −.2216 | .12682 | −1.75 | 0.081 | −.47016, .026969 | 57.48 |
| Economic status | −.064963 | .060829 | − 1.07 | 0.286 | −.18419, .054261 | 16.853 |
| Highest educational level | −.0072728 | .0074648 | − 0.97 | 0.330 | −.021904, .0073582 | 1.8867 |
| Occupation | .0023869 | .003225 | 0.74 | 0.459 | −.003934, .0087079 | −.61922 |
| Mass media | −.0023342 | .0049994 | − 0.47 | 0.641 | −.012133, .0074647 | .60553 |
| Marital status | .01427 | .021143 | 0.67 | 0.500 | −.02717, .055711 | − 3.702 |