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PLoS One
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10.1371/journal.pone.0308104
PONE-D-23-29356
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Geographical variation and predictors of missing essential newborn care items during the immediate postpartum period in Ethiopia: Spatial and multilevel count analyses
Spatial patterns and predictors of essential newborn care in Ethiopia
https://orcid.org/0000-0002-5719-4294
Hailegebireal Aklilu Habte Conceptualization Data curation Formal analysis Methodology Software Supervision Visualization Writing – original draft Writing – review & editing 1 *
Kitila Aiggan Tamene Formal analysis Methodology Writing – original draft Writing – review & editing 2 3
1 School of Public Health, College of Medicine and Health Sciences, Wachemo University, Hosanna, Ethiopia
2 Centre for Sustainability, University of Otago, Dunedin, New Zealand
3 Department of Preventive and Social Medicine, University of Otago, Dunedin, New Zealand
Abajobir Amanuel Editor
African Population and Health Research Center, ETHIOPIA
Competing Interests: The authors have declared that no competing interests exist.

* E-mail: akliluhabte57@gmail.com
6 9 2024
2024
19 9 e030810419 9 2023
16 7 2024
© 2024 Hailegebireal, Kitila
2024
Hailegebireal, Kitila
https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Background

Essential Newborn care (ENC) is a High-quality universal newborn health care devised by the World Health Organization for the provision of prompt interventions rendered to newborns during the postpartum period. Even though conducting comprehensive studies could provide a data-driven approach to tackling barriers to service adoption, there was a dearth of studies in Ethiopia that assess the geographical variation and predictors of missing ENC. Hence, this study aimed to identify geographical, individual, and community-level predictors of missing ENC messages at the national level.

Methods

This study used the 2016 Ethiopian Demographic and Health Survey, by using a weighted sample of 7,590 women who gave birth within two years prior to the survey. The spatial analysis was carried out using Arc-GIS version 10.7 and SaTScan version 9.6 statistical software. Spatial autocorrelation (Moran’s I) was checked to figure out the non-randomness of the spatial variation of missing ENC in Ethiopia. Six items of care used to construct a composite index.0of ENC uptake were cord examination, temperature measurement, counselling on danger signs, counselling on breastfeeding, observation of breastfeeding, and measurement of birth weight. To assess the presence of significant differences in the mean number of ENC items across covariates, independent t-tests and one-way ANOVA were performed. Finally, a multilevel multivariable mixed-effect negative binomial regression was done by using STATA version 16. The adjusted incidence rate ratio (aIRR) with its corresponding 95% CI was used as a measure of association and variables with a p-value<0.05 were identified as significant predictors of ENC.

Results

The overall prevalence of missing ENC was 4,675 (61.6%) (95% CI: 60.5, 62.7) with a significant spatial variation across regions. The majority of Somali, Afar, south Amhara, and SNNPR regions had statistically significant hotspots for missing ENC. The mean (±SD) number of ENC items received was 1.23(±1.74) with a variance of 3.02 indicating over-dispersion. Living in the poorest wealth quintile (aIRR = 0.67, 95%CI: 0.51, 0.87), lack of Antenatal care (aIRR = 0.52, 95%CI: 0.49, 0.71), birth at home (aIRR = 0.27, 95% CI: 0.17, 0.34), living in rural area (aIRR = 0.39, 95% CI: 0.24, 0.57) were significant predictors of ENC uptake.

Conclusion

The level of missing ENC was found to be high in Ethiopia with a significant spatial variation across regions. Hence, the government and policymakers should devise strategies for hotspot areas to improve women’s economic capabilities, access to education, and health-seeking behaviours for prenatal care and skilled delivery services to improve ENC uptake.

The author(s) received no specific funding for this work. Data AvailabilityThe data for this study were obtained from the DHS program with a reasonable request. Because the DHS office doesn’t allow to sharing of the data with other third parties, the one who needs the data supporting the findings of this study can get it in anonymized form from the DHS website at https://www.dhsprogram.com upon reasonable request. The authors did not have any special access privileges that others would not have.
Data Availability

The data for this study were obtained from the DHS program with a reasonable request. Because the DHS office doesn’t allow to sharing of the data with other third parties, the one who needs the data supporting the findings of this study can get it in anonymized form from the DHS website at https://www.dhsprogram.com upon reasonable request. The authors did not have any special access privileges that others would not have.
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pmcIntroduction

The neonatal period (the first month of life) is the most vulnerable and critical period for a child’s survival, growth, and development [1]. Approximately one million babies died during the first 24 hours of life in 2019, accounting for almost three-quarters (75%) of all neonatal deaths globally [2]. About 2.4 million newborns died during the neonatal period in 2020, with approximately 6700 newborn deaths every day, which represented nearly half (47%) of all under-5 deaths [2]. Sub-Saharan Africa(SSA) and Central and Southern Asia(CSA), with neonatal mortality rates (NNM) of 27 and 23 per 1000 live births, respectively, accounted for 43% and 36% of global neonatal deaths [2, 3]. A child born in SSA is ten times more likely than a child born in a high-income country to die in the first month [2]. Ethiopia has had significant achievement in reducing under-5 mortality rates by 71% over the last two decades, from 204 deaths per 1,000 live births in 1990 to 59 deaths per 1,000 live births in the 2019 mini EDHS report [4, 5]. However, the decline in NNM from 58 deaths per 1000 live births to 29 deaths per 1000 live births between 2000 and 2016 has not been satisfactory [4]. Even so, it has risen to 33 deaths per 1,000 live births in 2019 [4].

The postpartum period (PPP), which begins immediately after delivery and lasts up to six weeks (42 days), is an important time for women, babies, partners, parents, carers, and families [6]. The majority of neonatal deaths in developing countries including Ethiopia were due to a lack of quality essential newborn care (ENC), especially within the first two days of birth [2]. Thus, the World Health Organization (WHO) recently devised global recommendations on the timing and contents of postnatal care (PNC) for mothers and newborns, in resource-limited settings to ensure a positive postnatal experience [6]. One of the basic elements of PNC aimed at improving newborn survival is the provision of easy, low-cost, and less time-consuming ENC in the immediate PPP [7].

Essential Newborn care (ENC) is a WHO strategic approach for the provision of a constellation of interventions rendered to newborns during the immediate PPP [7, 8]. It is a High-quality universal newborn health care that entails prompt care at the time of birth and throughout the neonatal period, regardless of the place of delivery [8, 9]. It comprises measurement of body weight, temperature monitoring, hygienic cord care, early and exclusive breastfeeding, evaluation for danger signs, and preventive services like immunization [2, 7]. Findings showed that providing quality ENC is a cost-effective strategic approach that results in a considerable reduction in early and late neonatal death [10–12].

Despite its importance in the reduction of NNM, 29.3%, 32.3%, 35.5%, and 31% of women in Nepal [13], India [14], Rwanda [15], and Tanzania[16] missed ENC, respectively. However, a recent systematic review meta-analysis in Ethiopia revealed that the uptake of ENC services was found to be low at 48.77% [17]. Inadequate intrapartum (skilled delivery service) and postpartum care (like ENC) accounted for a steady reduction in neonatal deaths in Ethiopia [4, 18]. The government has been striving to meet the third Sustainable Development Goal (SDG3), which is aimed at ensuring healthy lives and promoting well-being for all people through the provision of adequate maternal and newborn health services [19]. ENC service delivery at the health facility and community level is one approach to meeting this ambitious goal [20].

Despite several studies on ENC uptake in Ethiopia, none investigated the spatial distribution of missing service usage and its predictors at the individual and community levels by using a large population. Even though a recent study attempted to examine the spatial distribution, it primarily focused on women who received ANC [9] and may have failed to provide a clear picture of ENC. Thus, the current study used a relatively larger sample size of women who were eligible for PNC and employed spatial (a hot spot and a geographically weighted regression (GWR) analysis) and multilevel count analytic approaches. A hotspot analysis was performed to identify regions with a high proportion of women who missed ENC, followed by a GWR to identify potential predictors that lead to regional disparities in missing the service. In addition, a multilevel approach was done to identify factors at the individual and community levels that contribute to missing ENC items. Conducting such comprehensive analyses could provide a data-driven approach to comprehending and reducing the barriers to service uptake [21]. The findings will enable stakeholders to strengthen their efforts in addressing the impediments to service uptake by designing geographical, individual, and community-focused effective interventions to ensure a positive postnatal experience.

Methods and materials

Data source, study design, and period

This study used the 2016 Ethiopian Demographic and Health Survey (EDHS) report; a population-based, nationally representative survey collected from January 18 to June 27, 2016. The country is located at 30−150 N latitude and 330−480 E longitude. The country has a total surface area of 1,112,000 km2 and has boundaries defined on the west by Sudan, on the east by Somali and Djibouti, on the north by Eritrea, and on the south by Kenya. Nine regions (Tigray, Afar, Amhara, Oromia, Somali, Benishangul-Gumuz, Southern Nation Nationality and People’s Region (SNNPR), Gambella, and Harari) and two self-administrative cities (Addis Ababa and Dire Dawa) were included in the survey [22]. The data were obtained from the women’s (IR) file contained in the 2016 EDHS report.

Population of the study

The source populations were all women who responded to a query about receiving a postnatal check-up within two months. The study population, on the other hand, were mothers who had complete information on the uptake of each essential newborn care within the first two days following delivery. A total of 8,490 respondents were excluded from the study due to a lack of information on service usage (missing values).

Sampling procedure and data collection tools

Study participants were selected through a stratified two-stage cluster sampling technique, where each region was divided into urban and rural areas. In the first stage, 645 clusters or enumeration areas (202 urban and 443 rural areas) were selected randomly. Then, a fixed number of 28 households with eligible women were selected per cluster based on an equal probability systematic selection. The survey design and methodology were addressed as well in the 2016 EDHS [22]. The Global Positioning System (GPS) was used to obtain the geographic coordinates of each survey cluster [22, 23]. To assure the confidentiality of respondents, the geographical locations(latitude and longitude) were randomly displaced. The greatest displacement was two kilometers (km) for all urban and five kilometers (km) for 99% of rural clusters. The remaining 1% of rural clusters have been displaced up to a 10-kilometer distance [24]. Data were collected from all eligible women using the Woman’s Questionnaire, which includes socio-demographic and economic information, obstetric characteristics, and maternal health service usage.

Measurement of variables of the study

Outcome variable

The outcome variable for this study was the uptake of essential newborn care services during the immediate postpartum period (PPP). The measurement was based on the receipt of six essential services: (i) cord examination (m78a_1), (ii) Temperature measurement (m78b_1), (iii.) Counselling on danger signs (m78c_1) (iv) Counselling on breastfeeding (m78d_1), (v) Observation of breastfeeding (m78e_1), and measurement of birth weight (m19_1). There were yes, and no response options for each question. For the sake of analysis, the categories were confined to Yes (= 1) and No (= 0). A composite index of essential newborn care (ENC) has been created based on the responses, which is a count of the number. The variable had a minimum and maximum value of zero and six, respectively. Finally, women with a value of ’0’ were considered as ’missing ENC service,’ whilst those who scored one or more were considered to have ‘received ENC’, and the spatial analyses were focused on those who did not receive the service [9, 25].

Explanatory variables

After reviewing related and current literature, potential predictors of ENC were selected from the data set and nested at the individual and community levels [7, 25–27] (Table 1).

10.1371/journal.pone.0308104.t001 Table 1 List of possible predictors of missing essential newborn care items during the immediate postpartum period in Ethiopia as extracted from the EDHS 2016 report.

Variables	Description	Category	
Age	The respondent’s age, expressed in years, at the time of the survey.	15–19,

20–34

35–49*

	
Marital status	Percentage of women according to the current status of marriage or cohabitation.	In marital relationships*

Not in a marital relationship

	
Level of Education	Percent distribution of women ages 15–49 by the highest level of schooling attended or completed.	No education

Primary

Secondary/higher*

	
Family size	Number of household members at the time of data collection	≤5*

>5

	
Sex of head of Household	Percent distribution of households by sex of head of household	Female

Male

	
Wealth index	Calculated using straightforward information on a household’s ownership of certain goods, such as televisions and bicycles; housing materials; livestock, crop production, and access to water, sanitation, and hygiene	Richest*

Richer

Middle

Poorer

Poorest

	
Parity	The number of living children the woman had at the time of the survey	Nulliparous

Primiparous

Multiparous

Grand multiparous*

	
Antenatal care	Number of women who received antenatal care for their last birth, which was initially reported in continuous form and then grouped as no antenatal care, 1 visit, 2–3 visits, 4+ visits	No ANC visit

One visit

Two-three visits

Four and more visits*

	
Pregnancy status during last childbirth	Percentage of births to women aged 15 to 49 in the five years preceding the survey, including current pregnancies, by planning status of the last pregnancy—(i) wanted then, (ii) wanted later, or (iii) not wanted at all.	Unwanted (ii& iii)

Wanted (i) *

	
Place of delivery	Percent distribution of live births in the past 5 years by place of delivery.	Health facility*

Home

	
Media exposure	The number of women aged 15 to 49 who are exposed to specific media at various frequencies, such as reading a newspaper, watching television, and listening to the radio.	Not at all

Less than once a week

At least once a week*

	
Autonomy in decision-making a	The total number of married women between the ages of 15 and 49 who make decisions for their own health care, major household buys, and visits to family or relatives.	Low

high*

	
	Community level factors		
Residence	The area where respondents lived when the survey was conducted.	Urban*

Rural

	
Region	The geographically delineated area where the woman was resided at the time of the survey. Three categories were created as Small periphery regions (Afar, Somali, Benishangul, and Gambella), Major central regions (SNNPRs, Tigray, Amhara, and Oromia) and Metropolitans (Addis Ababa, Dire Dawa, and the Harari region)	Small periphery

Major central regions

Metropolitans*

	
*reference category

a Autonomy in decision-making: was assessed by using three questions about who makes the final decision for the family on large property purchases, visits to relatives, and health care. The response categories were (i) woman alone, (ii) woman and husband/partner, (iii) husband/partner alone, (iv) someone else, and (v) others. For each question, responses (i) or (ii) got a score of 1, indicating good decision-making capacity, whereas the remaining responses received a score of 0, indicating weak decision-making capacity. All the responses were summed to yield an overall score ranging from 0 to 3. Finally, a composite score had been divided into two distinct groups: low and high for "0 to 2" and "3" scores [28, 29].

Data management and statistical analysis

STATA version 16, ArcGIS version 10.7, and SaTScan version 9.6 were used to analyze the data. The data were weighted to minimize under- or over-representation during strata-specific selection during the survey. This is vital to obtain a reliable estimate and draw proper inferences[30]. The weighted proportions of an ENC and its predictors were computed in STATA and prepared in Microsoft Excel 2016 (CSV format) before being loaded into ArcGIS 10.7 for further spatial analysis. Descriptive statistics such as frequency and percentage of different variables were estimated and displayed using texts, and tables.

Spatial analyses

Initially, the data containing the variable of interest in CSV format were imported into ArcGIS version 10.8 and combined with the GPS data (shape file). After that, the event data was converted to a shape file and displayed in an XY plane (geographically coordinated system). Projections of the geographically coordinated data to the projected coordinate data were performed before the analysis.

Spatial autocorrelation (Global Moran’s I)

The global spatial autocorrelation was estimated using Moran’s index to decide whether missing ENC in Ethiopia was dispersed, clustered, or randomly distributed. In general, a Moran’s I value close to 1 suggests significant positive autocorrelation (missing ENC was clustered/non-random), whereas a Moran’s I value close to -1 shows significant negative autocorrelation (missing ENC was dispersed) across enumeration areas (EAs). On the other hand, the value near zero implies that the spatial distribution of missing ENC was random (independence between EAs or no spatial autocorrelation) [31, 32]. Accordingly, Moran’s I value was statistically significant (p<0.05) which indicates the spatial distribution for missing ENC is non-random (clustered) [32].

Spatial interpolation

The spatial interpolation method is used to predict the likelihood of missing ENC in unsampled areas based on sampled EAs. There are multiple geostatistical and deterministic interpolation techniques, and for this study, ordinary Kriging was performed since it optimizes the weight and has a low residual and mean square error [33, 34].

The spatial scan statistical (SaTScan) analysis

A SaTScan analysis was carried out to show significant hot spots of missing ENC. The Bernoulli-based model was employed to detect the significant spatial clusters with no ENC since it uses a scanning window that moves across the study area [35]. To fit the Bernoulli model, women who missed ENC were treated as cases, while those who received the service were treated as controls. SaTScan statistics scanned gradually across the space to identify the number of observed and expected observations inside the window at each location. The default maximum spatial cluster size of 50% of the population was used as an upper limit, allowing both tiny and big clusters to be recognized. Using 999 Monte Carlo replications, the primary, secondary, and other significant clusters were identified and ranked based on the likelihood ratio test (LLR). A potential cluster, in the scanning window with the highest LLR and a significant p-value was selected as the high-performing cluster for being a case (missing ENC).

Hot spot analysis (Gettis-Ord Gi* statistics)

Getis-Ord Gi* statistics were carried out to identify significant hot spot and cold spot areas for missing ENC. The z-score was estimated to figure out the statistical significance of clustering, and the level of significance was set at p-value<0.05 with a 95% CI. Cold spot and hot spot were declared at z-score was less than -1.96 and greater than +1.96, respectively [36, 37].

Spatial regression analysis

Spatial regression analysis incorporates global (ordinary list squares) and local (geographically weighted regression) techniques [38, 39].

Ordinary least square (OLS) analysis

The Ordinary Least Squares (OLS) regression model is a global model that predicts only one coefficient per independent variable throughout the whole study area. The compliance of all assumptions was assessed to ensure the reliability of the findings in this model. First, the coefficients of the intercept and predictors have to be statistically significant having a positive or negative sign. Also, the presence of multicollinearity among explanatory variables should be confirmed by examining their variance inflation factors (VIF), and variables with VIF > 10 were considered multicollinear and iteratively excluded from the model [40, 41]. Furthermore, the Koenker Bp statistic was used to determine if the model could be employed for a geographically weighted regression (GWR) analysis. In the current study, the Koenker statistics were significant (p-value<0.001), and GWR analysis was required to examine the distribution of key variables.

Geographically weighted regression (GWR)

Unlike OLS, which fits a single linear regression equation to all of the clustered data, GWR selects data from neighbouring features, therefore the GWR coefficient has different values for each cluster [42]. Variables with p-values<0.05 in the OLS model were selected for GWR and discussed based on their coefficients.

Multilevel generalized linear model (GLM)

Due to the hierarchical nature of the EDHS data, where women were nested inside families and households were nested within clusters, ordinary one-level regression models were not appropriate, and hence multilevel modelling was used. Carrying out a multilevel analysis for such hierarchical data allows us to minimize biased parameter estimation [43].

Because the number of ENC items received is a non-negative integer (count), most recent thinking in the field suggests using GLM models with a Poisson link as a model of choice [44–46]. However, Poisson regression has an assumption, called the assumption of equidispersion, requiring the variance of the count response variable should be equal to its mean [45, 46]. The mean and variance of the count outcome variable in the current study were 1.23 and 3.02, respectively, indicating the presence of over-dispersed. Thus, a multilevel mixed-effect negative binomial regression model is appropriate for such an over-dispersed outcome variable [46–48].

Model building and selection

Fixed effects. To look into the presence of statistically significant differences in the mean number of ENC items across each categorical variable, independent t-tests and one-way analysis of variance (ANOVA) were performed. Those variables with p-values<0.05 were incorporated into a multilevel negative binomial regression, where significant predictors of ENC were determined. Finally, the incident rate ratio (IRR) with a 95% confidence interval was reported, and statistical significance was determined at a p-value<0.05.

Random effects. Four distinct models were fitted using a multilevel approach. Model one (null model) is devoid of any explanatory variables. The second and third models comprised solely individual and community-level characteristics. The fourth (full) model included and accounted for all factors at the individual and community level factors. The Intraclass Correlation Coefficient (ICC), Median Odds Ratio (MOR), and Proportional Change in Variance (PCV) were estimated to measure the random effects (variability in ENC uptake between and across clusters).

ICC quantifies the degree of heterogeneity of ENC between clusters and estimated as: ICC=varbVarb+Var(w);

Where Var(b) is the variance at the group level and Var(w) refers to the variance of the distribution used in the negative binomial link function, which is π2/3 ≈3.29.

The proportion of change in variance (PCV) measures the proportion of the total observed individual variation that is explained by the between-cluster variations and estimated as PCV=(Va-Vb)Va*100,

where, Va is the variance of the initial model (null model), and Vb = variance of the subsequent models (models 2, 3, and 4). The value lies between 0 and 1 (0 < PCV < 1) or 0 and 100% (0 < PCV < 100%).

The median odds ratio (MOR) represents the change in odds of missing ENC items when moving from one cluster to another while holding individual-level predictors constant.

Model fitness. Deviance = -2 * (Log Likelihood (LL), Schwarz’s Bayesian Information Criterion (BIC), and Akaike’s information criterion (AIC) were used to determine the best model. Finally, the fourth model with the lowest deviance, AIC, and BIC values was chosen as the best-fit model for the current study (Table 5).

Ethical consideration and consent to participate. Following registration at the DHS Programme website with possible justification, ICF International provided written permission to use both the DHS and GPS datasets. The data obtained were used only for the registered research and were not shared with anyone other than the co-authors. The DHS also declared that informed consent was obtained from all subjects and/or their legal guardian during the primary data collection. Furthermore, as this is secondary data, the Institutional Review Board (IRB) of Wachemo University College of Medicine and Health Sciences declared that no formal ethics approval was required. However, the IRB ensured that the research approach was ethically compliant with national and international standards.

Results

Background characteristics of the respondents

The findings of this study were based on a total weighted sample of 7,590 women. The mean (±SD) age of women was 29.25 (±6.84), with over half (50.4%) of them belonging to the age group of 25–34 years. Three-quarters (75.8%) of women in the poorest wealth quintile and 85.5% of women without ANC missed ENC services. In addition, 68.2% of rural women and 72.0% of women with no formal education missed ENC service. Addis Ababa and Afar regions exhibited the highest (3.7) and lowest (0.41) mean number of ENC contents, respectively. In addition, there were statistically significant differences in the mean number of ENC services received across the educational level, wealth index, residence, region, place of delivery, and media exposure (p<0.001) (Table 2).

10.1371/journal.pone.0308104.t002 Table 2 Overall proportion of missing ENC and mean distribution of receiving ENC items across different characteristics of women in Ethiopia, EDHS 2016.

Variable categories	Total [Weighted frequency (%)]	Missed ENC	Mean number of ENC items received	
n(%)	p-value	Mean (95% CI)	p-value	
Current age						
15–24	1,804(23.8)	1,021(56.6)	0.036	1.23(1.15, 1.30)	0.021a	
25–34	3,826(50.4)	2,307(60.3)	1.30(1.24, 1.36)	
35–49	1,959(25.8)	1,347(68.8)	1.09(1.01, 1.16)	
Regions						
Major central regions	6,899(90.9)	4,354(63.1)	<0.001	1.18(1.12, 1.23)	<0.001a	
Peripheral	441(5.81)	299(67.7)	0.73(0.68, 0.78)	
Metropolitans	249(3.3)	23(9.1)	2.46(2.34, 2.58)	
Religion						
Orthodox	2,882(38.0)	1,465(50.8)	<0.001	1.81(1.73, 1.89)	0.052a	
Muslim	2,824(37.2)	1,998(70.7)	0.93(0.88, 0.98)	
Protestant	1,651(21.8)	1,034(62.4	1.02(0.94, 1.11)	
Catholic	71(0.9)	48(67.4)	1.08(.63, 1.53)	
Traditional	96(1.3)	74(76.8)	0.26(0.13, 0.39)	
Others	64(0.8)	57(89.3)	0.31(0.23, 0.43)	
Marital status						
In marital relationship	7,020(92.5)	4,343(61.9)	0.032	1.20(1.15, 1.24)	0.061b	
Not in marital relationship	570(7.5)	333(58.4)	1.56(1.41, 1.71)	
Residence						
Urban	969 (12.8)	157(16.2)	<0.001	2.62(2.52, 2.72)	<0.001b	
Rural	6,621(87.2)	4,519(68.2)	0.86(0.82, 0.89)	
Wealth index combined						
Poorest	1,651(21.8)	1,252(75.8)	0.001	0.48(0.44, 0.52)	<0.001a	
Poorer	1,654(21.8)	1,188(71.8)	0.91(0.83, 0.99)	
Middle	1,588 (20.9)	1,036(65.2)	1.11(1.01, 1.21)	
Richer	1,426 (18.8)	879(61.6)	1.26(1.15, 1.38)	
Richest	1,269(16.7)	321(25.3)	2.62(2.52, 2.71)	
Educational status						
No education	4,791(63.1)	3,449(72.0)	0.001	0.75(0.71, 0.79)	<0.001a	
Primary	2,150(28.3)	1,142(53.1)	1.61(1.53, 1.69)	
Secondary and higher	649(8.6)	85(13.1)	2.74(2.61, 2.86)	
Head of household						
Male	6,474(85.3)	4,059(62.7)	0.003	1.19(1.14, 1.23)	0.991b	
Female	1,116(14.7)	617(55.3)	1.36(1.27, 1.45)	
Parity						
Nulliparous	49(0.7)	33(67.1)	<0.001	0.68(0.37, 0.99)	0.034a	
Primiparous	1,536(20.2)	688(44.8)	1.75(1.66, 1.84)	
Multiparous	3,478(45.8)	2,128(61.2)	1.27 (1.21, 1.33)	
Grand multiparous	2,527(33.3)	1,827(72.3)	0.83(0.76, 0.88)	
Frequency of ANC						
No visit	2,833(37.3)	2,421(85.5)	<0.001	0.32(0.29, 0.35)	<0.001a	
One visit	334(4.4)	225(67.4)	0.96(0.81, 1.12)	
2–3 visits	2,007 (26.5)	1,124(56.0)	1.20(1.13, 1.28)	
≥4 visits	2,415(31.8)	905(37.5)	2.15 (2.08, 2.23)	
Place of delivery						
Home	5,066(66.7)	4,217(83.2)	<0.001	0.35(0.32, 0.37)	<0.001b	
Health facilities	2,523(33.3)	459(18.2)	2.61(2.54, 2.68)		
Planning status of pregnancy						
Wanted	5,573(73.4)	3,377(39.4)	0.206	1.22 (1.17, 1.26)	0.820b	
Unwanted	2,016(26.6)	1,298(64.4)	1.27(1.18, 1.35)	
Ever terminate pregnancy						
Yes	680(8.7)	427(62.8)	0.636	1.28(1.14, 1.41)	0.448	
No	6,909(91.3)	4,248(61.5)	1.22(1.18, 1.26)	
Listen to radio						
Not at all	5,491(72.3)	3,679(67.0)	<0.001	0.94(0.90, 0.98)	0.031a	
Less than once a week	1,030(13.6)	503(48.9)	1.89(1.77, 2.02)	
At least once a week	1,069(14.1)	494(46.2)	2.23(2.09, 2.36)	
Watching TV						
Not at all	6,102(68.4)	4,176(68.4)	<0.001	0.85(0.81, 0.89)	<0.001a	
Less than once a week	764(10.0)	373(48.8)	1.71 (1.57, 1.86)	
At least once a week	724(9.5)	127(17.5)	2.90(2.78, 3.02)	
Reading newspaper						
Not at all	7,050(92.9)	4,566(64.8)	0.063	1.07(1.03, 1.11)	0.022 a	
Less than once a week	404(5.3)	79(19.6)	2.98(2.80, 3.16)	
At least once a week	135(1.8)	30(22.5)	2.86 (2.54, 3.19)	
Own mobile phone						
Yes	1,373(18.1)	446(32.4)	<0.001	2.34(2.25, 2.43)	<0.001b	
No	6,216(81.9)	4,230(68.0)	0.83(0.79, 0.87)	
Covered by Health Insurance						
Yes	317 (95.8)	152(47.8)	p<0.001	2.08(1.83, 2.32)	<0.001b	
No	7,272(4.2)	4,524(62.2)	1.19(1.16, 1.24)	
Autonomy in decision making						
Autonomous	5,395()	3,232(59.9)	<0.001	1.31(1.26, 1.36)	0.031b	
Non-autonomous	2,194()	1,443(65.8)	1.02(0.95, 1.09)	
Ease of distance to seek medical care						
Big problem	4,406(58.0)	3,111(70.6)	<0.001	0.82(0.77, 0.86)	<0.001b	
Not a big problem	3,183(42.0)	1,565(49.2)	1.69(1.63, 1.75)	
Access to money for seeking medical care						
Big problem	4,547(59.9)	3,096(68.1)	0.023	0.92(0.87, 0.96)	<0.001	
Not a big problem	3,043(40.1)	1,580(51.9)	1.64(1.57, 1.70)	
a p-values are based on an independent t-test

b p-values are based on a one-way Analysis of variance (ANOVA)

The level of missing ENC items and disparities across the regions

More than half, 61.6% (95% CI: 60.5, 62.7) of women missed at least one ENC item. The highest proportion of women who missed ENC was recorded in Oromia (73.6%), closely followed by Somali (73.1%) and Afar (72.7%) regions. The top three ENC items that the majority of women failed to receive were cord checks (90.5%), counselling about danger signs (89.3%), and temperature measurement (87.0%) (Table 3).

10.1371/journal.pone.0308104.t003 Table 3 The level of missing overall ENC and contents of care across regions of Ethiopia, EDHS 2016.

Regions	Women who missed each ENC item [Weighted frequency (%)]		
Birth weight measurement	Checking cord	Temperature measurement	Counselling on danger sign	Counselling on breastfeeding	Observing breastfeeding	Missing all items	
Tigray	359(66.8)	384(71.5)	357(66.5)	378(70.3)	252 (46.9)	207(38.6)	139(25.9)	
Afar	66(92.3)	69(97.0)	69(96.8)	67(94.9)	61(86.4)	55 (77.9)	52(72.7)	
Amhara	1,448(88.7)	1512(92.6)	1,407(86.2)	1,482(90.8)	1,145(70.2)	1,149 (70.4)	971(59.5)	
Oromia	2,770(88.5)	2909(92.9)	2,872(91.8)	2,954(94.4)	2,683(85.7)	2,603(89.2)	2,303(73.6)	
Somali	236(87.7)	255(94.9)	253(94.1)	261(97.3)	234(87.3)	226 (84.2)	197(73.1)	
Benishangul	60(74.0)	74(91.8)	71(87.8)	72(88.8)	57(71.2)	47(58.4)	41(50.4)	
SNNPR	1,331(83.2)	1477(92.3)	1,430(89.3)	1,386(86.6)	1,176(73.5)	1,160(72.5)	940(58.8)	
Gambella	14(65.1)	19(93.9)	19(91.3)	19(93.0)	16(78.6)	16(76.9)	10(47.1)	
Harari	10(56.3)	14(78.7)	14(80.3)	15(84.1)	12(66.0)	8(43.8)	5(29.1)	
Addis Ababa	22(11.0)	125(63.3)	89(44.7)	116(58.8)	52(26.4)	53(27.0)	7(3.6)	
Dire Dawa	16(48.6)	27(80.8)	26(79.6)	28(83.1)	19(59.6)	22(65.8)	10(31.1)	
Total	6,331(83.4)	6867(90.5)	6,607(87.0)	6,778(89.3)	5,712(75.2)	5,549(73.1)	4,675(61.6)	

Spatial analysis results

Spatial distribution of missing ENC among respondents

Somali, Afar, Western Oromia, and Gambella had a larger proportion of neonates who did not receive ENC. Tigray, Addis Ababa, and the Eastern border of Amhara, on the other hand, had a low rate of missing ENC (Fig 1).

10.1371/journal.pone.0308104.g001 Fig 1 Spatial distribution of missing ENC in Ethiopia, EDHS 2016.

Spatial autocorrelation of missing ENC

The global spatial autocorrelation analysis revealed that the spatial distribution of missing ENC was non-random (i.e. there was significant spatial variation) across the country (global Moran’s I = 0.49, p<0.001). The clustered patterns (on the right sides) suggest that missing ENC occurred at a high rate throughout the study area (Fig 2).

10.1371/journal.pone.0308104.g002 Fig 2 The global spatial autocorrelation of missing ENC in Ethiopia, EDHS 2016.

Incremental autocorrelation

To determine the average nearest neighbour and minimum and maximum distance band, the incremental spatial autocorrelation over a series of distances depicted by a line graph with a corresponding z-score was performed. With a starting distance of 121803 meters, a total of 10 distance bands were found, with the first highest peak (clustering) observed at 151367.66 meters (Fig 3).

10.1371/journal.pone.0308104.g003 Fig 3 The incremental autocorrelation of missing ENC in Ethiopia, EDHS 2016.

Hot spot (Getis-Ord Gi*) analysis

As evidenced by hot spot analysis, Somali, central and southwest Afar, the southern part of Amhara, southwest Oromia, and the north and eastern portions of SNNPR have a high rate of missing ENC. Tigray, Addis Ababa, and Dire Dawa, on the other hand, had a low percentage of missing ENC (Fig 4).

10.1371/journal.pone.0308104.g004 Fig 4 Hot spot and Cold spot analysis of missing ENC across regions in Ethiopia, EDHS 2016.

Spatial interpolation

The spatial distribution of missing ENC for places where data were not collected was estimated using the ordinary Kriging technique. The highest predicted prevalence of missing ENC(red-shaded) was found in southern Somali, North and South Afar, Southwest and central Oromia, and parts of Addis Ababa and Gambella. In contrast, the expected proportion of high ENC uptake (green-shaded) includes the entire Tigray region, and central parts of Addis Ababa, Gambella, Dire Dawa, and Harari (Fig 5).

10.1371/journal.pone.0308104.g005 Fig 5 Ordinary Kriging interpolation of the spatial distribution of missing ENC in Ethiopia, EDHS 2016.

Spatial scan statistical (SaTScan) analysis

The SaTScan spatial analysis identified fifteen statistically significant groups of SaTScan clusters with a high proportion of newborns missing ENC. This means that the prevalence of missing ENC was higher inside the SaTScan circular window than outside of it. In addition, the analysis identified a total of 333 significant clusters that accounted for missing ENC, of which 78 and 42 were found in the first and second most likely clusters respectively. The first most likely cluster located at geographical coordinates of (5.330795 N, 41.837597 E) with a 427.4 Km radius, and LLR of 82.86 at p<0.001 showed that newborn within the area had a 41% (RR = 1.41) higher risk to miss ENC than their counterparts outside the area (Table 4).

10.1371/journal.pone.0308104.t004 Table 4 The most likely SaTScan clusters of areas with a high prevalence of missing ENC among postpartum women in Ethiopia, EDHS 2016.

Most likely clusters	Enumeration areas (clusters) identified	Number of clusters	Population	No. of case	Coordinates / Radius	Relative risk	LLR	P-Value	
1st most likely cluster	556, 394, 480, 187, 520, 318, 278, 208, 164, 358, 377, 85, 289, 286, 472, 138, 452, 7, 492, 422, 543, 92, 490, 198, 171, 95, 34, 146, 82, 497, 518, 123, 405, 562, 521, 588, 553, 26, 468, 316, 458, 601, 213,398, 319, 576, 313, 619, 529, 365, 600, 21, 245, 445, 232, 589, 12, 214, 372, 634, 251, 32, 182, 573, 476, 391, 574, 524, 239, 122, 308, 216, 578, 215, 116, 22, 408, 148	78	1033	746	(5.330795 N, 41.837597 E)/427.38 km	1.41	82.86	<0.001	
2nd most likely cluster	138, 164, 85, 358, 146, 492, 92, 490, 543, 278, 171, 198, 95, 318, 77, 187, 497, 556, 520, 629, 521, 588, 553, 458, 480, 208, 214, 251, 573, 239, 269, 116, 22, 394, 378, 630, 568, 33, 277, 286, 527, 289	42	495	396	(5.589269 N, 44.175032 E) / 443.03 km	1.53	77.63	<0.001	
3rd most likely cluster	4, 632, 75, 596, 440, 366, 178, 499, 205, 427, 334, 570, 348, 599, 544, 389, 368, 241, 55, 547, 191, 571, 344, 276, 332, 189, 254, 37, 249, 620, 488, 307, 135	33	400	313	(11.845228 N, 41.915793 E) / 237.67 km	1.49	53.33	<0.001	
4th most likely cluster	403, 24, 429, 167, 456, 382, 120, 73, 516, 431, 375, 158, 169, 3, 512, 132, 474, 38, 206, 109, 361, 482, 531, 627, 229, 176, 163, 545, 350, 218, 10, 515, 292, 602, 498, 259, 541, 615, 494, 460, 548, 267, 510, 199, 386, 327, 415, 246, 533, 559, 640, 152, 354, 617, 312, 591, 616, 36, 150, 184, 401, 66, 279, 572, 628, 638, 423, 478, 183, 517	70	817	556	(11.157729 N, 37.668699 E) / 206.74 km	1.30	37.11	<0.001	
5th most likely cluster	131, 16, 2, 250, 301, 323, 328, 356, 367, 379, 42, 48, 525, 530, 540, 561, 625, 641, 72, 9, 96, 618, 266, 309, 435, 536, 370, 507, 592, 260, 104	26	360	270	(9.370004 N, 42.102751 E)/ 3855.29 km	1.39	35.19	<0.001	
6th most likely cluster	62, 411, 432, 586, 486, 447, 489, 227, 76, 142, 555, 280, 502, 294, 154, 118, 174, 234, 262, 177, 207, 577, 161, 399, 558, 331, 23, 306, 338, 477, 113, 272, 223, 41, 119	35	456	329	(8.246355 N, 36.621500 E) / 154.70 km	1.36	33.31	<0.001	
7th most likely cluster	182, 574, 232, 32, 21, 316, 398, 600	8	122	106	(5.973339 N, 38.182217 E) / 43.89 km	1.62	30.63	<0.001	
8th most likely cluster	476, 506, 412, 122, 333, 245, 372, 529, 71, 49, 491, 51, 230, 93, 564, 39, 484, 453, 336, 319, 441	20	267	194	(8.888553 N, 40.744565 E) / 127.63 km	1.36	20.12	<0.001	
9th most likely cluster	134, 263, 192, 117	4	53	49	(14.179123 N, 39.980749 E) / 28.29 km	1.71	19.15	0.021	
10th most likely cluster	610	1	22	22	(9.370004 N, 42.102751 E) / 0 km	1.85	13.54	0.001	
11th most likely cluster	1, 566	2	32	30	(9.505470 N, 42.438628 E) / 5.85 km	1.74	12.55	0.0026	
12th most likely cluster	235, 585, 127	3	48	42	(13.750028 N, 39.991260 E) / 15.05 km	1.62	12.46	0.0028	
13th most likely cluster	562, 213, 619, 123	4	62	51	(7.634301 N, 39.484475 E) / 50.25 km	1.53	11.00	0.011	
14th most likely cluster	172	1	17	17	(13.248133 N, 40.043685 E) / 0 km	1.85	10.46	0.018	
15th most likely cluster	425, 80	2	28	26	(13.351814 N, 38.353591 E) / 38.75 km	1.72	10.36	0.021	

Results of spatial regression

The global ordinary least square (OLS) analysis results

The OLS model is the first step toward choosing the appropriate predictors for the spatial variation of missing ENC. As a result, lack of formal education, giving birth at home, lacking ANC, and never watching television were found to be associated with missing ENC. There was no sign of multicollinearity among the selected predictors (mean VIF = 1.40, minimum VIF = 1.19, and maximum VIF = 1.94). Furthermore, the adjusted R2 = 0.718 from the OLS global model output indicated that the four predictors explained 71.8% of the variation in missing ENC. Jarque-Bera statistics with p-value>0.05 (p = 0.448) suggest that the model prediction was not biased (the requirement for residual normality was met). The Koenker statistics in the model, on the other hand, showed a statistically significant p-value (p<0.001), showing that the regression model is inconsistent across the study area, implying the necessity for the GWR model to estimate the model parameters properly (Table 5).

10.1371/journal.pone.0308104.t005 Table 5 Summary of OLS results for not receiving ENC in Ethiopia, EDHS 2016.

Variable	Coefficient	SE	t-Statistic	Probability	Robust SE	Robust t-statistics	Robust probability	VIF	
Intercept	0.303	0.043	2.41	0.016	0.047	2.19	0.028	---	
Women who gave birth at home	0.674	0.032	16.57	<0.001	0.042	12.82	<0.001	1.19	
Women without formal education	0.220	0.035	6.13	<0.001	0.039	5.61	<0.001	1.62	
Women without ANC	0.501	0.033	14.93	<0.001	0.036	13.87	<0.001	1.76	
Women who never watch television	0.171	0.040	4.24	<0.001	0.048	3.51	<0.001	1.94	
OLS Diagnostics	
Number of Observations:	622	Akaike’s Information Criterion (AICc)	-349.68	
Multiple R2	0.709	Adjusted R2 [d]:	0.718	
Joint F-Statistic	377.40	Prob(>F), (7,599) degrees of freedom	<0.001	
Joint Wald Statistic	2548.58	Prob(>chi-square),(7) degrees of freedom	<0.001	
Koenker (BP) Statistic	41.62	Prob(>chi-square), (7) degrees of freedom	<0.001	
Jarque-Bera Statistic	1.60	Prob(>chi-square), (2) degrees of freedom	0.448	

Geographically weighted regression analysis

To deal with this violation of the stationarity assumption of the global (OLS) model, the local (GWR) model was fitted to offer realistic estimates. The GWR analysis outperformed the global model (OLS) significantly. The AICc value in the GWR model reduced from -349.68 in the OLS model to -401.11. The adjusted R2 in GWR was greater than the OLS one, showing that the local model enhanced its ability to forecast hotspots of missing ENC. The highest range of R2 was shown in central Addis Ababa, central and western Oromia, and the northern part of SNNPR regions. As compared to other regions, the model is less explained by the predictors in the southern part of the Benishangul Gumuz region (Fig 6).

10.1371/journal.pone.0308104.g006 Fig 6 The spatial mapping of local adjusted R-square of the GWR model in Ethiopia, 2016.

As the proportion of women who gave birth at home increased, so did the proportion of missing ENC in most parts of Afar and Somali, in some parts of Oromia and Gambella, and the eastern border of Benishangul Gumuz. On the other hand, the positive and weaker relationship between home birth and missing ENC was observed in most parts of Tigray, eastern and central Amhara, and some parts of Addis Ababa (Fig 7).

10.1371/journal.pone.0308104.g007 Fig 7 GWR coefficients of the proportion of women who gave birth at home for predicting missing ENC messages in Ethiopia, EDHS 2016.

This study also highlights the space-dependent relationship between missing ENC and education status. As the proportion of women with no formal education increases, the likelihood of missing ENC also increases in the entire Somali, west Afar, most parts of SNNPR, and the Northern part of Gambella regions (Fig 8).

10.1371/journal.pone.0308104.g008 Fig 8 GWR coefficients of the proportion of women without formal education for predicting missing ENC messages in Ethiopia, EDHS 2016.

Women who did not have ANC had a strong link with women who did not have ENC. As the proportion of women who did not attend ANC rose, so did the number of missing ENC in Afar, Somali, Northwest Gambella, south of the SNNPR, and northern and southern Amhara regions (Fig 9).

10.1371/journal.pone.0308104.g009 Fig 9 GWR coefficients of the proportion of women without ANC for predicting missing ENC messages in Ethiopia, EDHS 2016.

Results of multilevel mixed effect negative binomial regression

Random effect (measures of variation)

In the null model, the value of ICC 0.261 which implies that 26.1% of the total variability in the receipt of ENC items was explained by the difference between clusters. Furthermore, variation at the individual and community levels accounted for 11.1% (ICC = 0.111, p<0.001) and 14.1% (ICC = 0.141, p<0.001), respectively, of the variation in the mean number of ENC items. Individual, and community-level factors together accounted for 51% of the mean variation seen in the null model (PCV = 73.2%). The values of AIC, BIC, and Deviance decreased as we progressed from model 1 (the empty model) to model 4 (the full model), indicating that the final model fitted throughout the study had adequate goodness of fit. Finally, the fourth model with the lowest deviance (17708.0) was chosen as the best model fit (Table 6).

10.1371/journal.pone.0308104.t006 Table 6 Results of a multivariable mixed-effect negative binomial regression to identify the determinants of uptake of ENC items in Ethiopia, EDHS2016.

Variable categories	Model I (null model)	Model II (individual-level factors)	Model III (community-level factors)	Model-IV (full model)	
		IRR(95%CI)	IRR(95%CI)	IRR(95%CI)	
Current age					
35–49		1.01(0.83, 1.22)		0.95(0.78, 1.15)	
25–34		1.07(0.93, 1.23)		1.05(0.91, 1.20)	
15–24		Ref.		Ref.	
Wealth index					
Poorest		0.54(0.42, 0.69)**		0.60(0.46, 0.79) **	
Poorer		0.59(0.46, 0.75)**		0.67(0.51, 0.87) **	
Middle		0.83(0.69, 1.01)		0.79(0.62, 1.02)	
Richer		0.85(0.71, 1.04)		0.81(0.62, 1.01)	
Richest		Ref.		Ref.	
Educational status					
No education		0.71(0.59, 0.86)**		0.73(0.60, 0.89) **	
Primary		0.85(0.72, 1.04)		0.87(0.73, 1.02)	
Secondary and higher		Ref.		Ref.	
Head of household					
Male		0.86(0.76, 0.98)*		0.89(0.78, 1.01)	
Female		Ref.		Ref.	
Parity					
Nulliparous		0.68(0.35, 1.35)*		0.69(0.34, 1.36)	
Primiparous		1.15(0.95, 1.41)		1.12(0.92, 1.36)	
Multiparous		0.95(0.81, 1.11)		0.92(0.79, 1.08)	
Grand multiparous		Ref.		Ref.	
Frequency of ANC					
No visit		0.47(0.39, 0.56)**		0.52(0.49, 0.71) **	
One visit		0.83(0.66, 1.04)		0.83(0.66, 1.04)	
2–3 visits		0.88(0.79, 1.08)		0.92(0.76, 1.15)	
≥4 visits		Ref.		Ref.	
Place of delivery					
Home		0.20(0.17, 0.24)		0.27(0.17, 0.34) **	
Helath facility		Ref.		Ref.	
Listen to radio					
Not at all		0.95(0.79, 1.13)		0.93(0.77, 1.11)	
Less than once a week		0.98(0.82, 1.19)		0.96(0.79, 1.16)	
At least once a week		Ref.		Ref.	
Watching TV					
Not at all		0.89(0.74, 1.06)		0.98(0.82, 1.18)	
Less than once a week		1.15(0.96, 1.38)		1.25(0.97, 1.52)	
At least once a week		Ref.		Ref.	
Reading newspaper					
Not at all		1.15(0.93, 1.43)		1.14(0.91, 1.42)	
Less than once a week		1.21(0.94, 1.62)		1.28(0.99, 1.60)	
At least once a week		Ref.		Ref.	
Own mobile phone					
No		0.89(0.74, 1.05)		0.90(0.75, 1.07)	
Yes		Ref.		Ref.	
Covered by Health Insurance					
No		0.86(0.72, 1.09)		0.95(0.77, 1.16)	
Yes		Ref.		Ref.	
Autonomy in decision-making					
Non-autonomous		1.15(0.83, 1.05)		0.94(0.83, 1.06)	
Autonomous		Ref.		Ref.	
Distance to seek healthcare					
Big problem		0.84(0.75, 0.95)**		0.89(0.78, 1.02)	
Not a big problem		Ref.		Ref.	
Ease of access to money					
Big problem		0.97(0.85, 1.10)		0.96(0.85, 1.10)	
Not a big problem		Ref.		Ref.	
Regions					
Peripheral			0.44(0.36, 0.53)**	0.56(0.47, 0.66) **	
Major central regions			0.65(0.56, 0.76)**	0.83(0.71, 0.98)**	
Metropolitans			Ref.	Ref.	
Residence					
Rural			0.27(0.23, 0.32)**	0.39(0.24, 0.57) **	
Urban			Ref.	Ref.	
Random effects					
Variance	1.16	0.41	0.54	0.31	
ICC	0.261	0.111	0.141	0.086	
AIC	18847.6	17890.3	18544.6	16788.11	
BIC	18868.2	18089.8	18640.0	17063.3	
MOR	2.80	1.85	2.01	1.71	
PCV	Ref.	64.6%	53.4%	73.2%	
Model fitness					
Log-likelihood	-9420.8	-8177.2	-9319.5	-8854.0	
Deviance	18841.6	18354.4	18639.0	17708.0	
Key: Ref.: Reference category; aIRR = Adjusted Incidence Rate Ratio,

* statistically significant at p-value <0.05,

** statistically significant at p-value <0.001

Fixed effects: Predictors of receipt of ENC items

In the multivariable multilevel negative binomial regression analysis, wealth index, educational status, frequency of ANC, residence, and region were identified as significant predictors of receiving ENC.

The incidence rate of getting ENC was lowered by 40% (aIRR = 0.60, 95%CI: 0.46, 0.79) and 33% (aIRR = 0.67, 95%CI: 0.51, 0.87) among women in the poorest and poorer wealth quintiles, respectively than women in the richest wealth quintile. Women without formal education were 27% less likely to receive items of ENC than those who attend secondary or higher education (aIRR = 0.73, 95%CI: 0.60, 0.89). As compared to women who received 4 or more ANC visits, the chance of receiving ENC items fell by 48% among those who did not receive any ANC visits (aIRR = 0.52, 95%CI: 0.49, 0.71). Women who gave birth at home had a 73% lower likelihood of receiving ENC items (aIRR = 0.27, 95% CI: 0.17, 0.34) than women who gave birth in health facilities. Region and residence were the two community-level factors that were identified as significant predictors of ENC. Women who lived in the peripheral regions had 44% less chance of receiving ENC items (aIRR = 0.56, 95% CI: 0.47, 0.66) as compared to women who lived in metropolitan one. Similarly, women who resided in the rural part of the country were 61% less likely to receive ENC items as compared to their urban counterparts (aIRR = 0.39, 95% CI: 0.24, 0.57) (Table 6).

Discussion

It is vital to investigate the spatial distribution and predictors of essential newborn care utilization at the national level to design a targeted intervention to reduce neonatal mortality and increase satisfaction and utilization of maternal and neonatal health services by women [26]. In this study, the prevalence of missing ENC was found to be 61.6% (95% CI: 60.5, 62.7) which is higher than a systematic review and meta-analysis conducted in Ethiopia (51.2%) [17], and similar studies conducted in Nepal (29.3%) [13], India (32.3%) [14], Rwanda(35.5%) [15], and Tanzania(31%) [16]. The disparity could be attributed to differences in socioeconomic and sociocultural characteristics, availability and accessibility of health service infrastructure, and maternal health service coverage, between countries.

In addition, spatial global Moran’s analysis found that the percentage of women who didn’t receive ENC varied geographically. As per hot spot analysis, statistically significant hotspot areas for missing ENC were Somali, central and southwest Afar, south Amhara, and the eastern border of SNNPR regions. Previous studies revealed that maternal and neonatal health service uptake was low in those regions [49–53]. This clustering might be due to a variety of factors. To begin, as compared to other regions, those two regions, particularly Afar and Somali, are known to have a shortage of healthcare facilities, limited healthcare providers, and a lack of medical supplies and equipment to provide ENC services [54, 55]. In addition, they are located in remote and arid areas with inadequate road infrastructure and transportation services, making it difficult for both women and health care providers to access and deliver immediate postnatal care services, potentially leading to high coverage of missing ENC [56]. Furthermore, because the majority of the people in these regions live pastoral or partly nomadic lives, it may be difficult for postpartum women to access adequate ENC services because their places of residence change over time.

In multilevel mixed effect negative binomial and Geographically weighted regression analyses, having no formal education, giving birth at home, and lack of ANC were identified as significant predictors of not receiving ENC in Ethiopia. In addition, living in the poorest wealth quintile, being a rural resident, and living in a peripheral region were also identified as significant determinants of the uptake of ENC items in a multilevel regression model.

Not receiving ANC for the last pregnancy was found to be strongly associated with missing ENC items. This was supported by studies conducted in Bangladesh [57], Nigeria [58], Ghana [59], Uganda [60], East Africa [61] and Ethiopia [62]. In addition, studies conducted in Asia revealed that information on newborn care practices provided to pregnant women and their families during ANC visits resulted in enhanced ENC practices such as complete cord care, complete thermal care, and breastfeeding initiation [63]. In addition, ANC links pregnant women with skilled healthcare providers who can assist with safe deliveries and immediate newborn care [64]. Lack of ANC visits could result in missed opportunities for newborn care education and information, reduced access to skilled birth attendants, and inadequate birth preparedness and complication readiness, all of which can contribute to a higher likelihood of missing ENC, which is critical for ensuring the health and survival of newborns [58].

Home birth was also identified as a significant predictor of missing ENC packages. This was in tandem with the findings of studies conducted elsewhere [65–67]. This might be due to a variety of reasons. First, giving birth at home potentially can lead to difficulty in accessing skilled healthcare providers in the immediate postpartum period, and this results in missing ENC [65]. As compared to births at health facilities, those at home have a lower or no likelihood of receiving postnatal care, education, and counselling, and being closely monitored by healthcare providers resulted in missing vital ENC components. Thus, efforts should focus on increasing access to skilled birth attendants through improving healthcare and transportation infrastructure, educating communities about the importance of facility deliveries, and addressing cultural and socioeconomic factors that hinder delivery choices [68, 69].

The current study revealed that the risk of receiving ENC items was lower among women who never attended formal education. This was supported by studies conducted in LMICs [70], Pakistan, Ghana [59], and Ethiopia [71]. This could be due to, women without formal education may have limited access to information about ENC and its importance, which can lead to suboptimal care. Furthermore, a lack of formal education may result in a lower socioeconomic status and accompanying financial constraints, as well as a lack of autonomy in decision-making, all of which can be linked to limiting access to the resources needed and healthcare services for ENC. As a result, improving access to formal education is essential for addressing those challenges, particularly in areas where formal education is limited.

Similarly, living in a household with the poorest wealth quintile was revealed to be a statistically significant predictor of not receiving ENC. This was supported by studies conducted in India [72], Nepal [73], and Ethiopia [74]. Those women in the poorest wealth quintile are more likely to experience financial barriers in accessing maternal healthcare, especially ANC, skilled delivery, and PNC services all of which are vital entry points to get ENC services. Furthermore, poverty and financial constraints can put a strain on women and families by limiting access to information and the ability to make health-care decisions [75].

The study has the following strengths. First, the findings were based on an analysis of nationally representative data, making the findings more generalizable. This study is also enriched by the findings of Hot Spot, geographically weighted regression, and multilevel mixed-effect negative binomial regression analysis. As a result, the findings can assist government and program planners in designing geographical, individual, and community-focused public health interventions based on the identified predictors for tackling barriers to ENC. On the other hand, the finding also should be interpreted in light of limitations. To begin, to safeguard the confidentiality of respondents or the community, the geographical coordinates of clusters were displaced by up to 2km in urban areas, 5km for most rural clusters, and 10km for 1% of rural clusters; this may alter estimated cluster effects in the spatial regression. Second, because of the cross-sectional nature of EDHS data, it is hard to infer a temporal/causal relationship between the variables. Furthermore, as the data were based on the retrospective interviews of women who responded to receipt of PNC for their last birth, the findings may be subject to recall bias. Finally, the data were based on self-report and this tends to face recall- and social desirability bias which may underestimate or overestimate the true association.

Conclusion

The level of missing ENC during immediate PPP was found to be high in Ethiopia with a significant spatial variation across regions. Statistically significant hotspot areas for not receiving ENC were northern Somali, central and southwest Afar, the southern part of Amhara, and the eastern border of SNNPR regions. Living in the poorest wealth quintile, being a rural resident, having no formal education, giving birth at home, and lack of ANC were identified as significant predictors of not receiving ENC. Hence, the government and policymakers should devise strategies for hotspot areas to improve women’s economic capabilities, access to education, and health-seeking behaviours for prenatal care and skilled delivery services in order to improve ENC uptake.

We are grateful to ICF macro (Calverton, USA) for providing the 2016 DHS data of Ethiopia.

Abbreviations

AIC Akaike’s information criterion

ANC Antenatal Care

CSA Central Statistical Agency

EDHS Ethiopian Demographic and Health Survey

ENC Essential Newborn Care

GWR Geographically Weighted Regression

IRR Incidence Rate Ratio

OLS Ordinary Least Square

PNC Postnatal Care

PPP Postpartum Period

WHO World Health Organization

10.1371/journal.pone.0308104.r001
Decision Letter 0
Abajobir Amanuel Academic Editor
© 2024 Amanuel Abajobir
2024
Amanuel Abajobir
https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Submission Version0
24 Apr 2024

PONE-D-23-29356Spatial patterns and predictors of missing essential newborn care items during the immediate postpartum period in Ethiopia: Spatial and multilevel count analyses of 2016 Demographic Health SurveyPLOS ONE

Dear Dr. Habte,

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Additional Editor Comments:

Overall, the manuscript provides a comprehensive overview of the neonatal care landscape in Ethiopia, particularly focusing on the postnatal period and essential newborn care (ENC) services. Here's a breakdown of the review focusing on the quality of English, writing, and content:

Quality of English and writing:

There are a few instances where sentences could be refined for clarity and flow. For instance, in the Methods and Materials section, sentences like "Respondents were selected using a stratified two-stage cluster sampling technique, having each region divided into urban and rural areas" could be rephrased for smoother reading, such as "Respondents were selected through a stratified two-stage cluster sampling technique, where each region was divided into urban and rural areas." Such minor adjustments can enhance readability without altering the technical content.

Additionally, there are some instances of lengthy sentences and complex structures that could be simplified for better comprehension, especially for readers not familiar with the subject matter. Breaking down complex sentences into smaller, digestible parts can improve readability and understanding.

Content:

Introduction: The introduction provides a comprehensive overview of the significance of the neonatal period and the challenges faced, especially in low-resource settings like Ethiopia. It effectively sets the stage for the study by highlighting the gap in essential newborn care utilization. However, it should be clear and concise in setting the stage!

Methods and Materials: Some parts could benefit from concise explanations to avoid overwhelming the reader with technical details. For example, the explanation of spatial autocorrelation and spatial interpolation could be simplified for clarity.

Results/Discussion: See above for the quality of writing.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

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Reviewer #1: Partly

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2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

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Reviewer #1: No

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Reviewer #1: No

**********

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Reviewer #1: Title: Spatial patterns and predictors of missing essential new born care items during the immediate postpartum period in Ethiopia: Spatial and multilevel count analyses of 2016

Demographic Health Survey is a well-written manuscript. Some comments to consider before publication are listed below.

General comments

- This 2016 EDHS data is too old, we do have MEDHS of 2019 data, is it justifiable that you can still go back to 2016 while new data available? considering trends could enable you to use all data…..probably

- Your abstract method section does not tell us which ANOVA you used

- Why SPSS 16, while you can do 25 or more what is the secret?

- The abstract does not list what is the essential newborn care or defining variables

- Abstract result focuses only on spatial results like there are no other variables

- Include the success number with percent in abstract and result sections …..(()60%)

- The level ENC is lower in your abstract compared to nothing……. Please avoid partial statements as this is a common problem throughout. For example, the government and policymakers should tailor strategies to hotspot areas by implementing activities and interventions…. What strategies…??? What implementation??

- Just avoid general statements and non-practical recommendations or conclusions, this makes the study nonsense.

Introduction

- However, the drop in NNM has been more static, falling from 58 deaths per 1000 live births in 2000 to 29 deaths per 1000 births in 2016. This statement is not clear. I do know how something static could have this much variation. Please, follow the academic way of writing, your writing lacks details and makes partial statements and it is not to the point of focus. You need to go through the whole document and make clear sense of those limited ideas.

- Is PPP just 42 days? Exactly what information is necessary for a mother during postpartum?

- intrapartum and postpartum care remained mostly responsible for a steady reduction in neonatal death in Ethiopia……what are those intrapartum and postpartum care missing in Ethiopia?

- Your finding indicates 60% of ENC is missing, but your literature does not have any information related to this excepting million global deaths. You need to reconstruct your introduction according to your main objective.

- Based on this evidence the gap for which you conducting this study is clearly identified and you need to deal more.

Methods

Your methods look nice but consider the following

- Have clear data preparation and how you handled missing or if other difficulties exist as this data has many gaps

- Provide a clear procedure for your analysis and assumptions for low scholars' understanding. You have that for spatial analysis but not for others

- How do you apply OLS with dichotomous data?

Results

- You have very large result presentations, you may need to make a summary of results at the end

- Somalia, Afar, and Gambella are usually underperforming in most studies what is different about them?

Discussion

- Result comparison could make more sense if you can make a more focus comparison with similar setups and reasonably compare how that is common is most developing countries. Something is missing in your initial paragraph – focus

Conclusion

- I already commented on how to make the conclusion more practical earlier, thus, apply here.

-

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Reviewer #1: No

**********

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10.1371/journal.pone.0308104.r002
Author response to Decision Letter 0
Submission Version1
3 May 2024

A point-by-point response to editor and reviewers

Authors’ Response to Academic Editor

Dear: Amanuel Abajobir, PhD, Academic Editor, Plos One

We thank you for a thorough reading and constructive comments and suggestions on our manuscript and for the opportunity to revise and resubmit. We are pleased to submit the revised version of the manuscript titled “Geographical variation and predictors of missing essential newborn care during the immediate postpartum period in Ethiopia: Spatial and multilevel count analyses” for your consideration in the special collection of Plos One. The comments of the editors and the reviewers were highly insightful and enabled us to greatly improve the quality of our manuscript. In this revised manuscript we made substantial changes to address your concerns in a point-by-point response. We appreciate your time and look forward to your response and we are very keen to incorporate further comments, if any, for the betterment of the final manuscript.

On the following pages, you will find our responses to the comments and suggestions raised by the esteemed editor and reviewer.

Sincerely,

Aklilu Habte (MPH)(corresponding author)

aklilihabte57@gmail.com

Response to Journal requirements

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming.

Response: we already prepared the manuscript as per the journal requirement and again we rechecked the compliance towards it during the submission of our revised manuscript.

2. In the online submission form, you indicated that [The data for this study were obtained from the DHS program with a reasonable request. Thus, the one who needs the data supporting the findings of this study can get it in anonymized form from the DHS website at https://www.dhsprogram.com upon reasonable request in the same manner as the authors did.].

All PLOS journals now require all data underlying the findings described in their manuscript to be freely available to other researchers, either 1. In a public repository, 2. Within the manuscript itself, or 3. Uploaded as supplementary information.

This policy applies to all data except where public deposition would breach compliance with the protocol approved by your research ethics board. If your data cannot be made publicly available for ethical or legal reasons (e.g., public availability would compromise patient privacy), please explain your reasons on resubmission and your exemption request will be escalated for approval.

Response: The DHS data policy doesn’t allow sharing of the dataset with third parties for other than initially registered purposes. Thus, we suggested the readers access the data on the above-mentioned link based on the reasonable request.

3. We note that Figure(s) [1,4,5,6,7,8 and 9,] in your submission contain [map/satellite] images which may be copyrighted. All PLOS content is published under the Creative Commons Attribution License (CC BY 4.0), which means that the manuscript, images, and Supporting Information files will be freely available online, and any third party is permitted to access, download, copy, distribute, and use these materials in any way, even commercially, with proper attribution. For these reasons, we cannot publish previously copyrighted maps or satellite images created using proprietary data, such as Google software (Google Maps, Street View, and Earth). For more information, see our copyright guidelines: http://journals.plos.org/plosone/s/licenses-and-copyright.We require you to either (1) present written permission from the copyright holder to publish these figures specifically under the CC BY 4.0 license, or (2) remove the figures from your submission:

1. You may seek permission from the original copyright holder of Figure(s) [1,4,5,6,7,8 and 9,] to publish the content specifically under the CC BY 4.0 license.

We recommend that you contact the original copyright holder with the Content Permission Form (http://journals.plos.org/plosone/s/file?id=7c09/content-permission-form.pdf) and the following text:

“I request permission for the open-access journal PLOS ONE to publish XXX under the Creative Commons Attribution License (CCAL) CC BY 4.0 (http://creativecommons.org/licenses/by/4.0/). Please be aware that this license allows unrestricted use and distribution, even commercially, by third parties. Please reply and provide explicit written permission to publish XXX under a CC BY license and complete the attached form.”

Response: We appreciate your concern to assure the ethical issues. However, all the aforementioned figures (1,4,5,6,7,8 and 9) in our manuscript are not copyrighted rather they are the result of spatial analysis that we have run in ArcGIS and SaTScan software. The GPS and DHS data that contain Shapefile and other relevant variables were obtained from the DHS office by explaining the objective of the study through online requests. Then, in order to get those figures, we import the relevant data extracted from the 2016 Ethiopian Demographic Health Survey reports and the shapefile of Ethiopia obtained from the 2016 Ethiopian Central Statistical Agency (CSA).To indicate this, we already cited the source of the shapefile alongside each figure. The shape file that we used to construct the figures can be accessed by one of the following links:

1. https://data.humdata.org/dataset/cb58fa1f-687d-4cac-81a7-655ab1efb2d0

2. https://gadm.org/download_country.html

Therefore, the maps presented in our study are not copyrighted rather they were the outputs of our spatial analysis results which are the result of those Shapefiles and projected CVS files in ArcGIS. This is the actual procedure that we employed in our present and earlier studies, as well as other Ethiopian researchers. Again we assure you that the figures presented in our study are not copyrighted but rather our spatial analysis results.

Response to Additional Editor Comments:

General Comment: Overall, the manuscript provides a comprehensive overview of the neonatal care landscape in Ethiopia, particularly focusing on the postnatal period and essential newborn care (ENC) services. Here's a breakdown of the review focusing on the quality of English, writing, and content:

Response: Thank you for your positive and constructive comments and suggestions we got all of them crucial in the improvement of the manuscript. Accordingly, we tried to respond to your possible suggestions as follows:

Comment 1: There are a few instances where sentences could be refined for clarity and flow. For instance, in the Methods and Materials section, sentences like "Respondents were selected using a stratified two-stage cluster sampling technique, having each region divided into urban and rural areas" could be rephrased for smoother reading, such as "Respondents were selected through a stratified two-stage cluster sampling technique, where each region was divided into urban and rural areas." Such minor adjustments can enhance readability without altering the technical content. Additionally, there are some instances of lengthy sentences and complex structures that could be simplified for better comprehension, especially for readers not familiar with the subject matter. Breaking down complex sentences into smaller, digestible parts can improve readability and understanding.

Response: Thank you for your insightful suggestions. We tried to correct some vague and complex sentences and highlighted them throughout the "Revised Manuscript with Track Changes"

Comment 2: Methods and Materials: Some parts could benefit from concise explanations to avoid overwhelming the reader with technical details. For example, the explanation of spatial autocorrelation and spatial interpolation could be simplified for clarity.

Response: Thank you for your suggestion. Initially, we did this intending to make the statements more clear to readers. Now, we entirely concur with your point of view because detailed explanations can be confusing to readers, thus we attempted to simplify certain difficult remarks.

Thank you for your constructive comments and suggestions, which we got as valuable input in the improvement of the manuscript. We received all of them as a valuable contribution to our ongoing work. In the following section, we tried to respond to all the possible comments and suggestions from reviewer #1

_____________________________END________________________________________

THANK YOU!!!

Authors’ Response to Reviewer#1

General comment: Demographic Health Survey is a well-written manuscript. Some comments to consider before publication are listed below.

Response: Dear Reviewer 1, thank you very much for taking the time to review our work and for your positive feedback. We received your thoughtful, and generous review, along with helpful feedback and suggestions, as a valuable contribution to our ongoing work. We have tried to address all the possible comments and suggestions raised by you in the following session.

Comment 1: Your abstract method section does not tell us which ANOVA you used

Response: thank you for your meticulous review. It was to mean a One-way ANOV and we have corrected and highlighted it in the ‘Abstract’ section of the "Revised Manuscript with Track Changes" Page 2, Line 50

Comment 2: Why SPSS 16, while you can do 25 or more what is the secret?

Response: It was not SPSS v16 it was STATA version 16 which was the most updated version at hand during the time of our analysis.

Comment 3: The abstract does not list what is the essential newborn care or defining variables

Response: Thank you for your thoughtful inquiry. As the abstract should be with a limited amount of words, initially we tried to make it short and precise. Now, as per your suggestion, we incorporated the items and highlighted them in the ‘Abstract’ section of the "Revised Manuscript with Track Changes" Page 2, Line 46-49

Comment 4: Abstract result focuses only on spatial results like there are no other variables

Response: We tried to incorporate the results of both spatial and multilevel analysis in a more short and precise way. For your clarity, the results other than spatial analysis were highlighted in the ‘Abstract’ section of the "Revised Manuscript with Track Changes" Page 2, Lines 58-63. Comment 5: Include the success number with percent in abstract and result sections …..(()60%)

Response: We have corrected and highlighted it in the ‘Abstract’ section of the "Revised Manuscript with Track Changes" Page 2, Line 56.

Comment 6: The level ENC is lower in your abstract compared to nothing……. Please avoid partial statements as this is a common problem throughout. For example, the government and policymakers should tailor strategies to hotspot areas by implementing activities and interventions…. What strategies…??? What implementation?? Just avoid general statements and non-practical recommendations or conclusions, this makes the study nonsense.

Response: Thank you for your inquiry and constructive suggestions. From the start, we concluded that Ethiopia had a higher level of missing ENC. The conclusion was reached after comparing and contrasting the current statistics with previous large-scale studies undertaken in Ethiopia and other countries. For that matter, we kindly ask you to look into the ‘Discussion’ section of the "Revised Manuscript with Track Changes" Page 21, Lines 454-457. Regarding our recommendation, it lacks specificity and thus we made an amendment and highlighted it in the ‘Abstract’ section of the "Revised Manuscript with Track Changes" Page 3, Lines 66-68

Comment 7: However, the drop in NNM has been more static, falling from 58 deaths per 1000 live births in 2000 to 29 deaths per 1000 births in 2016. This statement is not clear. I do know how something static could have this much variation. Please, follow the academic way of writing, your writing lacks details and makes partial statements and it is not to the point of focus. You need to go through the whole document and make clear sense of those limited ideas.

Response: It was to mean the figure was not satisfactory as per the government plan and to show it is vital to work on newborns. We have made amendments to the statement and highlighted it in the ‘Introduction’ section of the "Revised Manuscript with Track Changes" Page 3, Lines 81-82. We gave due emphasis to your comments and suggestions throughout the revised version of the manuscript and we have highlighted them.

Comment 8: Is PPP just 42 days? Exactly what information is necessary for a mother during postpartum?

Response: Yes, the postpartum period covers from the time of delivery to 42 days postpartum. However, our study mainly focuses on the contents of care provided during the immediate postpartum period (i.e. within 2 days following birth) which is the focus of DHS data. In addition, other preventive and curative services could be provided during PPP but they were not our current study’s interest.

Comment 9: intrapartum and postpartum care remained mostly responsible for a steady reduction in neonatal death in Ethiopia……what are those intrapartum and postpartum care missing in Ethiopia?

Response: Thank you for asking. The main intrapartum care was skilled delivery service and the postpartum one was essential newborn care services. We made slight amendments to the statement and highlighted it in the ‘Introduction’ section of the "Revised Manuscript with Track Changes" Page 3, Lines 104-106.

Comment 10: Your finding indicates 60% of ENC is missing, but your literature does not have any information related to this excepting million global deaths. You need to reconstruct your introduction according to your main objective.

Response: Thank you for your suggestion. Accordingly, we added some figures regarding the level of missing ENC from previously conducted large-scale studies. That statement was highlighted in the ‘Introduction’ section of the "Revised Manuscript with Track Changes" Page 3, Lines 101-104.

Comment 10: Based on this evidence the gap for which you conducting this study is clearly identified and you need to deal with more.

Response: thank you for your suggestion to strengthen the real gaps that were addressed by this study. Accordingly, we highlighted the gaps that were addressed by the current study in the last paragraph of the ‘Introduction’ section of the "Revised Manuscript with Track Changes" Page 4.

Comment 11: Have clear data preparation and how you handled missing or if other difficulties exist as this data has many gaps

Response: we have removed those respondents without any information on the uptake of PNC within 42 days. We have mentioned this in the ‘Population of the study’ section of the "Revised Manuscript with Track Changes" Page 5, Lines 138-142. Beyond that, we didn’t face any difficulty with missing values on other important covariates.

Comment 12: Provide a clear procedure for your analysis and assumptions for low scholars' understanding. You have that for spatial analysis but not for others

Response: Thank you for your insightful suggestion. We have mentioned the details of assumptions that we followed while running a generalized linear model (a multilevel negative binomial regression) in the ‘Data management and statistical analysis’ section of the "Revised Manuscript with Track Changes" Page 10, Lines 257-264.

Comment 13: How do you apply OLS with dichotomous data?

Response: The ordinary least square(OLS) that we applied in the current study was from the spatial regression dimension, not from the perspective of ordinary linear regression. we kindly ask you to look into the details of the spatial regression section.

Comment 14: You have very large result presentations, you may need to make a summary of results at the end

Response: thank you for your suggestion. However, the journal requirement doesn’t allow us to add the summary part to the result section. The only section to summarize our findings was the ‘Abstract’ section and we tried to summarize all the main findings here. By emphasizing your remarks, we attempted to make the result section more concise and precise by trimming some of the lengthy phrases.

Comment 15: Somalia, Afar, and Gambella are usual

Attachment Submitted filename: Response to reviewers.docx

10.1371/journal.pone.0308104.r003
Decision Letter 1
Abajobir Amanuel Academic Editor
© 2024 Amanuel Abajobir
2024
Amanuel Abajobir
https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Submission Version1
22 May 2024

PONE-D-23-29356R1Geographical variation and predictors of missing essential newborn care during the immediate postpartum period in Ethiopia: Spatial and multilevel count analysesPLOS ONE

Dear Dr. Habte,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Please submit your revised manuscript by Jul 06 2024 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

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An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

We look forward to receiving your revised manuscript.

Kind regards,

Amanuel Abajobir, PhD

Academic Editor

PLOS ONE

Journal Requirements:

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

Additional Editor Comments:

Although the revised version has addressed most of the comments, significant language edits are still required to meet the standards of scientific writing before it can be formally accepted for publication.

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

10.1371/journal.pone.0308104.r004
Author response to Decision Letter 1
Submission Version2
23 May 2024

A point-by-point response to editor and reviewers

Authors’ Response to Academic Editor

Dear: Amanuel Abajobir, PhD, Academic Editor, Plos One

We thank you for a thorough reading and constructive comments and suggestions on our manuscript and for the opportunity to revise and resubmit. We are pleased to submit the revised version of the manuscript titled “Geographical variation and predictors of missing essential newborn care during the immediate postpartum period in Ethiopia: Spatial and multilevel count analyses” for your consideration in the special collection of Plos One. The comments of the editors and the reviewers were highly insightful and enabled us to greatly improve the quality of our manuscript. In this revised manuscript we made substantial changes to address your concerns in a point-by-point response. We appreciate your time and look forward to your response and we are very keen to incorporate further comments, if any, for the betterment of the final manuscript.

Sincerely,

Aklilu Habte (MPH)(corresponding author)

aklilihabte57@gmail.com

Response to Journal requirements

1. Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

Response: Thank you for your reminder to look into the appropriateness of the references that we used for this work. Accordingly, we got all the references were relevant and none of them were retracted.

Response to Additional Editor Comments:

Comment 1: Although the revised version has addressed most of the comments, significant language edits are still required to meet the standards of scientific writing before it can be formally accepted for publication.

Response: Thank you for acknowledging that we addressed most of the comments raised by the reviewers and editor. As per your suggestion, we tried to give due emphasis to the grammatical and typological issues throughout the manuscript and we tried to correct and highlight them throughout the "Revised Manuscript with Track Changes"

Comment 2: While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org Please note that Supporting Information files do not need this step.

Response: Thank you for your suggestion. However, we initially submitted the figures as per the journal’s requirement and we want to assure you that they were PACE corrected figures.

Thank you for your constructive comments and suggestions, which we got as valuable input in the improvement of the manuscript. We received all of them as a valuable contribution to our ongoing work.

_____________________________END________________________________________

THANK YOU!!!

Attachment Submitted filename: Response to editor.docx

10.1371/journal.pone.0308104.r005
Decision Letter 2
Abajobir Amanuel Academic Editor
© 2024 Amanuel Abajobir
2024
Amanuel Abajobir
https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Submission Version2
3 Jul 2024

PONE-D-23-29356R2Geographical variation and predictors of missing essential newborn care during the immediate postpartum period in Ethiopia: Spatial and multilevel count analysesPLOS ONE

Dear Dr. Habte,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Please submit your revised manuscript by Aug 17 2024 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

We look forward to receiving your revised manuscript.

Kind regards,

Amanuel Abajobir, PhD

Academic Editor

PLOS ONE

Additional Editor Comments:

Please remove any reference to any 'ethnicity' in the 'Classification' of the submission system.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #2: (No Response)

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #2: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #2: Yes

**********

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The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #2: Yes

**********

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Reviewer #2: Yes

**********

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Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #2: The manuscript requires major editorial editing throughout. The cited references, abbreviations etc need to be spaced out from the words and figures consistently across the entire manuscript, including the tables. Please refer to a PLOS journal article for an example.

The analysis conducted is comprehensive, but the manuscript could be further improved.

Line 175, full name for abbreviation for BPCR.

Line 267, Line 271, Line 315, one or two-tailed test is to be stated.

Line 280, the sentence for Var(w) is to be revised. Var (w) refers to the variance of the standard logistic distribution used in the logistic link function.

Line 284, the PCV range and interpretation to be provided e.g. 0 < PCV < 1.

Line 286, more information for MOR to be provided e.g. quantify the unexplained cluster-level heterogeneity.

Line 369, typo p<000

Line 379, Line 391, Line 393, Line 396, R2, R squared, R-square is to be written as R^2 or R with 2 as superscript or R-squared. Need to be consistent/standardized.

Table 6 current age, the values o.83 and o.93 to be revised as 0.83 and 0.93 respectively.

References did not conform to the journal format.

**********

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Reviewer #2: No

**********

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

10.1371/journal.pone.0308104.r006
Author response to Decision Letter 2
Submission Version3
4 Jul 2024

A point-by-point response to editor and reviewers

Authors’ Response to Academic Editor

Dear: Amanuel Abajobir, PhD, Academic Editor, Plos One

We thank you for a thorough reading and constructive comments and suggestions on our manuscript and for the opportunity to revise and resubmit. We are pleased to submit the revised version of the manuscript titled “Geographical variation and predictors of missing essential newborn care during the immediate postpartum period in Ethiopia: Spatial and multilevel count analyses” for your consideration in the special collection of Plos One. The comments of the editors and the reviewers were highly insightful and enabled us to greatly improve the quality of our manuscript. In this revised manuscript we made substantial changes to address your concerns in a point-by-point response. We appreciate your time and look forward to your response and we are very keen to incorporate further comments, if any, for the betterment of the final manuscript.

On the following pages, you will find our responses to the comments and suggestions raised by the esteemed editor and reviewer.

Sincerely,

Aklilu Habte (MPH)(corresponding author)

aklilihabte57@gmail.com

Response to editors’ comment

1. Please remove any reference to any 'ethnicity' in the 'Classification' of the submission system.

Response: thank you so much for your suggestion. Accordingly, we removed it in the submission system during our submission to revised version of the manuscript.

_____________________________END________________________________________

THANK YOU!!!

Authors’ Response to Reviewer#2

Comment 1: The manuscript requires major editorial editing throughout. The cited references, abbreviations etc need to be spaced out from the words and figures consistently across the entire manuscript, including the tables. Please refer to a PLOS journal article for an example.

Response: Dear Reviewer 2, thank you very much for taking the time to review our work and for your positive feedback. We received your thoughtful, and generous review, along with helpful feedback and suggestions, and we have corrected all the raised editorial issues throughout the revised version of the manuscript. For your convenience, we made a highlight to show the space between the reference and words.

Comment 2: The analysis conducted is comprehensive, but the manuscript could be further improved.

Response: we appreciate your concerns. However, we assure you that the whole content of the manuscript was the mirror image of the analysis. We performed descriptive, multilevel, and spatial analyses and all results were well presented accordingly.

Comment 3: Line 175, full name for the abbreviation for BPCR.

Response: Thank you very much for your meticulous review. It was a typo error and we have corrected and highlighted it in the ‘Measurement of variables of the study’ section of the "Revised Manuscript with Track Changes" on page 6, Lines 174-175

Comment 4: Line 267, Line 271, Line 315, a one or two-tailed test is to be stated.

Response: we appreciate your insightful inquiry. We performed an independent t-test and one-way Analysis of variance (ANOVA) and we have corrected and highlighted it in the ‘data analysis’ section of the "Revised Manuscript with Track Changes" on page 10, Line 267

Comment 5: Line 280, the sentence for Var(w) is to be revised. Var (w) refers to the variance of the standard logistic distribution used in the logistic link function.

Response: thank you for your meticulous review and insightful suggestion. We have corrected and highlighted it in the ‘Data analysis’ section of the "Revised Manuscript with Track Changes" on page 10, Lines 280-281

Comment 6: Line 284, the PCV range and interpretation to be provided e.g. 0 <PCV < 1.

Response: thank you for your suggestion. We have added and highlighted it in the revised version of the manuscript, Lines 285-286, Page 10

Comment 7: Line 286, more information for MOR to be provided e.g. quantify the unexplained cluster-level heterogeneity.

Response: we have added the statement and highlighted it in the revised version of the manuscript, Lines 287-288, Page 10.

Comment 8: Line 369, typo p<000

Response: We have corrected and highlighted it on Line 371, Page 15

Comment 9: Line 379, Line 391, Line 393, Line 396, R2, R squared, R-square is to be written as R^2 or R with 2 as superscript or R-squared. Need to be consistent/standardized.

Response: Thank you for your meticulous review. We have corrected it as R2 and highlighted it as per your suggestion.

Comment 10: Table 6 current age, the values o.83 and o.93 to be revised as 0.83 and 0.93 respectively.

Response: we have corrected and highlighted it in Table 6 of the "Revised Manuscript with Track Changes" Page 19.

Comment 11: References did not conform to the journal format.

Response: Thank you so much for your suggestion. As the Plos One journal requirement is the Vancouver style we made citations accordingly. Beyond that, this is the reference style that we used during our prior publication experience at this journal.

Thank you for your constructive comments and suggestions, which we got as valuable input in the improvement of our manuscript. We received all of them as a valuable contribution to our ongoing work.

_________________________________________________________________________________________________________END_______________________________________

THANK YOU!!!

Attachment Submitted filename: Response to reviewers.docx

10.1371/journal.pone.0308104.r007
Decision Letter 3
Abajobir Amanuel Academic Editor
© 2024 Amanuel Abajobir
2024
Amanuel Abajobir
https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Submission Version3
17 Jul 2024

Geographical variation and predictors of missing essential newborn care items during the immediate postpartum period in Ethiopia: Spatial and multilevel count analyses

PONE-D-23-29356R3

Dear Author(s),

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Amanuel Abajobir, PhD

Academic Editor

PLOS ONE

10.1371/journal.pone.0308104.r008
Acceptance letter
Abajobir Amanuel Academic Editor
© 2024 Amanuel Abajobir
2024
Amanuel Abajobir
https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
19 Jul 2024

PONE-D-23-29356R3

PLOS ONE

Dear Dr. Hailegebireal,

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now being handed over to our production team.

At this stage, our production department will prepare your paper for publication. This includes ensuring the following:

* All references, tables, and figures are properly cited

* All relevant supporting information is included in the manuscript submission,

* There are no issues that prevent the paper from being properly typeset

If revisions are needed, the production department will contact you directly to resolve them. If no revisions are needed, you will receive an email when the publication date has been set. At this time, we do not offer pre-publication proofs to authors during production of the accepted work. Please keep in mind that we are working through a large volume of accepted articles, so please give us a few weeks to review your paper and let you know the next and final steps.

Lastly, if your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

If we can help with anything else, please email us at customercare@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr Amanuel Abajobir

Academic Editor

PLOS ONE
==== Refs
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18 Doherty T. , et al ., Reduction in child mortality in Ethiopia: analysis of data from demographic and health surveys. Journal of global health, 2016. 6 (2 ). doi: 10.7189/jogh.06.020401 29309064
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20 Federal Ministry of Health, Ethiopia, Essential Care for Every Baby Training Participants’ Manual, 2016
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22 Csa, I., Central statistical agency (CSA)[Ethiopia] and ICF. Ethiopia demographic and health survey, Addis Ababa, Ethiopia and Calverton, Maryland, USA, 2016. 1.
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