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. 2021 Sep 9;16(9):e0254146. doi: 10.1371/journal.pone.0254146

Magnitude, trends and determinants of skilled delivery from Kilite-Awlaelo Health Demographic Surveillance System, Northern Ethiopia, 2009- 2017

Haftom Temesgen Abebe 1,*, Mache Tsadik Adhana 2,#, Mengistu Welday Gebremichael 3,#, Kebede Embaye Gezae 1,‡, Assefa Ayalew Gebreslassie 2,‡
Editor: Frank T Spradley4
PMCID: PMC8428565  PMID: 34499647

Abstract

Background

The fundamental approach to improve maternal and neonatal health is increasing skilled delivery rate. Women giving birth at health institutions can prevent maternal and neonatal deaths by getting skilled birth attendance. In Ethiopia, despite a significant decrease in maternal mortality over the past decade, still a significant number of women give birth at home. Moreover, evidence from population-based longitudinal studies on skilled delivery is limited. Therefore, this study aims to investigate the magnitude, trend, and determinants of skilled delivery in Kilite-Awlaelo Health Demographic Surveillance System (KA-HDSS), Northern Ethiopia.

Method

Population-based longitudinal study design was conducted by extracting data for nine consecutive years (2009–2017) from KA-HDSS database. In order to measure the trends of skilled delivery, KA-HDSS data sets were analyzed (2009–2017). Bivariate and multivariate analyses were performed using STATA version 16. A multivariable binary logistic regression model was fitted to assess determinants of skilled delivery and odds ratio with 95% CI was used to assess presence of associations at a 0.05 level of significance.

Results

The skilled delivery rate have continuously increased among reproductive age women from 15.12% (95% CI: 13.30% - 17.09%) in 2010 to 95.85% (95% CI: 94.58% - 96.895%) in 2017. The skilled delivery rate becomes high (> = 82) in the period of 2014–2017. Education, residence, marital status, occupation and antenatal care (ANC) visits were the most important determinants for skilled delivery among reproductive age women during the period of high skilled delivery rate (2014–2017). Women urban dwellers had about 28 times (AOR = 27.66; 95% CI: 3.86–196.97) higher odds to deliver by skilled birth attendants than rural dwellers. Unmarried women who gave birth were 2.18 (AOR: 2.18; 95% CI: 1.30–3.64) times more likely to have skilled delivery service compared to those married. Likewise, women with four or more ANC visits were 3.2 times more likely to undergo skilled delivery service than those having no ANC visits (AOR: 3.16; 95% CI: 2.33–4.28). Moreover, women having at least a secondary education were 2 times more likely to have skilled delivery service compared to those women with no formal education (AOR = 2.10, 95% CI: 1.18–3.74).

Conclusion

Regardless of the importance of health facility delivery, a significant number of women still deliver at home attended by unskilled birth attendants. There has been a substantial increase in use of health facilities for delivery among women in the reproductive age. The factors affecting skilled delivery among reproductive age women were educational level, residence, marital status, occupation and use of ANC service. Maternal health related interventions are needed to change women’s attitudes towards skilled delivery. Moreover, ANC coverage should be increased to improve skilled delivery service.

Introduction

The skilled attendant is a health professional who may be a midwife, doctor, or nurse with midwifery and life-saving skills [1]. Skilled health personnel are competent maternal and newborn health professionals who are educated, trained and qualified based on national and international standards [2]. An estimated 289,000 women die per annum due to complications related to pregnancy and childbirth [3]. Two thirds of maternal deaths occur after delivery [4, 5]. Poor maternal and neonatal care results in 2.9 million neonatal deaths every year [6]. Of those global deaths 99% occurred in low- and middle-income countries including Ethiopia [7, 8]. The lifetime risk of dying in pregnancy situations are 1 in 30,000 in Sweden and 1 in 16 in sub-Saharan Africa [9].

The fundamental approach to improve maternal and neonatal health is increasing skilled delivery rate [10]. The demonstrated strategies to diminish maternal mortality are skilled birth attendance, referral for complications and universal availability of emergency obstetric care, such as Caesarian section [11]. Sustainable Development Goals (SDGs) goal three aims to decrease the global maternal mortality ratio to less than 70 per 100,000 live births and ensure universal access to sexual and reproductive health services by 2030. Despite the availability of access to healthcare service, the quality of care matters in the outcome of pregnancy.

Ethiopia has good progress in reducing maternal mortality. The Ethiopian Demographic and Health Surveys (EDHS) showed that Maternal Mortality Ratio (MMR) has dropped from 871 in 2000 to 676 in 2011 and then to 412 in 2016 per 100,000 live births, which is in line with the findings of the UN Inter-Agency Group (UN-IAG) that showed that the MMR had declined from 1,400 to 353 maternal deaths per 100,000 live births. The absolute number of women who died during pregnancy or childbirth had also decreased by nearly 75%, from 31,000 to around 11,000 from 1990 to 2015. [9, 10, 12, 13].

According to the EDHS report, the skilled delivery of the three surveys showed that 6% in 2005, 11% in 2011 and 28% in 2016. The skilled delivery of those surveys in Tigray were 6% in 2005, 12% in 2011 and 69% in 2016. This lags behind the health sector transformation plan of the country, which was set to be 90% [14–17].

Achieving “proportion of births attended by skilled health personnel” is Sustainable Development Goal 3. This requires strong and effective strategies, and accurate measurement and monitoring of progress for ending preventable maternal mortality [18]. Despite significant reduction in maternal mortality in the past decade, ending preventable maternal mortality (EPMM) remains an unfinished agenda and one of the world’s most critical challenges [18].

In the light of this evidence, we have assessed Kilite-Awlaelo Health and Demographic Surveillance System (KA-HDSS) source data base of Mekelle University College of Health Sciences, collected from 2009 to 2017, to understand the size and range of changing delivery trends in skilled delivery attendance [19]. So far few studies in Ethiopia have been conducted regarding skilled delivery [20–23]. Evidence from population based longitudinal studies on skilled delivery is limited. Besides, there is no information regarding the trend of skilled delivery over time. Thus, the study aimed to assess the magnitude, trend and determinants of skilled delivery using population based longitudinal data from KA-HDSS in Northern Ethiopia.

Materials and methods

Study setting and design

KA-HDSS is an ongoing open cohort study, located in Northern Ethiopia and hosted by Mekelle University. The site has three climatic zones which includes lowland, midland and high land. Administratively, it was established in 9 rural and 1 urban kebelles in April 2009 (a kebelle is the smallest administrative component in the country). At the beginning of the surveillance, baseline socio-demographic characteristics of 65,848 individuals living in 14,455 households were collected through a census. At the same time, a unique surveillance identification number was given to every enumerated cohort and household to facilitate linking information during longitudinal observation. In 2016, 2 urban kebelles were added as part of the study area and the number of household increased to 21,688. In 2017, the project has made 11 updates rounds with population of 101,146 living in 21,688 households in 12 kebeles (9 rural and 3 urban). A house to house visit is done to capture information regarding individuals, pregnancy observation, pregnancy outcomes, deaths, births and migration. Events are collected as it occurs and updated every six months [19].

Data sources and study population

The source of data for this study was from KA-HDSS. The study population for this study was all women who had at least one birth in KA-HDSS from April, 2009 to December, 2017.

Data extraction tool and study variables

Data regarding the skilled delivery were extracted mainly from pregnancy observation, pregnancy outcome, and relationship tables of KA-HDSS data considering the relevance of each explanatory variable on the prediction of skilled delivery rate in the population.

Dependent variable

The dependent variable in this study was skilled delivery. It was a dichotomized response as 1 if a woman gave birth by skilled birth attendants and 0 otherwise (if a woman gave birth by unskilled birth attendants).

Independent variables

The independent variables were classified as socio-demographic variables, and pregnancy outcome and related variables.

The socio-demographic variables are age, ethnicity, religion, marital status, occupation, level of education, and place of residence. The pregnancy outcome and related variables are age at pregnancy, number of ANC visits, bed net use, number of children born alive, number of children dead, number of previous pregnancy and previous pregnancy outcome.

Statistical data analysis

Data were cleaned and analysed in STATA version 15 statistical tool. The study population were described using frequency (percentage), mean (±standard deviation (sd)) depending on the nature of data (variables). A line graph was used to observe the trend of institutional delivery (number of skilled deliveries per 100) over time. Moreover, a cross-tabulation between each categorical independent variable and the outcome variable was done to check whether the expected cell counts were adequate or not. Besides, descriptive statistics, a rigorous statistical method was applied to identify the determinants of delivery in the study setting. Bivariate analysis was performed to assess the relationship between the dependent and independent variables.

A multivariable binary logistic regression analysis was fitted to identify the adjusted effect of each determinant on the skilled delivery among the study population of the specified study setting. The assumptions of multicollinearity between two or more independent variables were checked. Goodness of fit of the model was assessed using Hosmer-Lemeshow test. Decision regarding the statistical significance effect of independent variables on skilled delivery was made based on either the 95% CIs for AOR or associated P-values.

Ethical approval and consent to participate

Permission to access the data was obtained from Mekelle University KA HDSS via an agreement on the data sharing policy after ethical approval was obtained from Institutional Review Board (IRB) of Mekelle University, College of Health Sciences. Consent to participate was fully waived as the study participants were not directly involved in the study (i.e. an already existing data were utilized for analysis in the current study). Moreover, the confidentiality of data was kept as there were no personal identifiers used and neither the raw data nor the extracted data were passed to a third person (i.e. it is only used for the purpose of the study).

Results

Socio-demographic characteristics

Overall, 7,263 women were included in the study for a total of 11,925 observations for delivery in the last nine years (2009–2017). Of the 7,263 women, 3,842(52.89%) were Para I, 2,320(31.94%) were Para II, 966(13.30%) were Para III, 130(1.79%) were Para IV and 5(0.07%) were Para V. The mean and standard deviation of the women’s age at pregnancy who were included in the study was found to be 30.12±6.8 years. Almost all (99.3%) of the participants were Tigreans, and 7,164(98.6%) were also orthodox religion followers. Regarding their occupation, more than half (56.73%) were house wives. Moreover, 4,390(60.4%) of women had no formal education, and more than two thirds (68.9%) were married, 6,466(89.0%) were rural dwellers (Table 1).

Table 1. Socio-demographic characteristics of the women who delivery in the last nine years, Kilite-Awlaelo HDSS site, Northern Ethiopia, 2009–2017.

Socio demographic Frequency (%) Skilled delivery X2 test
Yes (%) No (%)
Residence of women (n = 7,263)
Rural 6,466(89.03) 3,693(57.11) 2,773(42.89) <0.001
Urban 797(10.97) 760(95.36) 37(4.64)
Ethnicity women (n = 7,263)
Tigray 7,214(99.33) 4,415(61.20) 2,799(38.80) 0.030
Amhara 16(0.22) 15(93.75) 1(6.25)
Oromo 31(0.43) 21(67.74) 10(32.26)
Other 2(0.03) 2(100.00) 0(0.0)
Religion (n = 7, 263)
Orthodox 7,164(98.64) 4,370(61.00) 2,794(39.00) <0.001
Muslim 96(1.32) 81(84.38) 15(15.62)
Catholic 3(0.04) 2(66.67) 1(33.33)
Maternal Education(n = 7,263)
Illiterate 4,390 (60.44) 2,244(51.12) 2,146(48.88) <0.001
Primary education 2,109(29.04) 1,573(74.58) 536(25.42)
Secondary education 667(9.18) 547(82.01) 120(17.99)
College and above 97(1.34) 89(91.75) 8(8.25)
Maternal Occupation(n = 7,263)
House wife 4,120(56.73) 2,051(49.78) 2,069(50.22) <0.001
Farmer 514(7.08) 313(60.90) 201(39.10)
Student 1,087(14.97) 885(81.42) 202(19.58)
Merchant 481(6.62) 423(87.94) 58(12.06)
Government employee 162(2.23) 142(87.65) 20(12.35)
Daily laborer 442(6.09) 296(66.97) 146(33.03)
Unemployed 129(1.78) 100(77.52) 29(22.48)
Other 328(4.52) 243(74.09) 85(25.91)
Marital status (n = 7,263)
Married 5,004(68.90) 2,733(54.62) 2,271(45.38) <0.001
Unmarried 1,724(23.74) 1,348(78.19) 376(21.91)
Others 535(7.37) 372(69.53) 163(30.47)
Age at pregnancy (n = 11,925)
15–19 584(4.90) 369(63.18) 215(36.82) <0.001
20–24 2,304(19.32) 1,393(60.46) 911(39.54)
25–29 2,738(22.96) 1,770(64.65) 968(35.35)
30–34 2,931(24.58) 1,856(63.32) 1,075(36.68)
35–39 2,233(18.73) 1,428(63.95) 805(36.05)
40–44 969(8.13) 656(67.70) 313(32.30)
45–49 166(1.39) 121(72.89) 45(27.11)
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Maternal health service utilization characteristics

Based on their ANC visits, 8,515 of 11,925 (71.40%) of pregnancies had at least one ANC visit. Of the women who had ANC visits, 2,234(26.24%) reached ANC 4 and above. Based on pregnancy outcomes, of the total observations, 11,593(97.22%), 178(1.49%) and 154(1.29%) had live births, abortion and still births, respectively. The median frequency of ANC visit was 2.5. Regarding gravidity, 2,567(35.34%) of women had history of 5 and above pregnancies (Table 2).

Table 2. Maternal health service utilization characteristics of the women who delivery in the last nine years, Kilite-Awlaelo HDSS site, Northern Ethiopia, 2009–2017.

Health services Frequency (%) Skilled delivery X2 test
Yes (%) No (%)
ANC attendance (n = 11,925)
Yes 8,515(71.40) 5,853(68.74) 2,662(31.26) <0.001
No 3,410(28.60) 1,740(51.03) 1,670(48.97)
Number of ANC (n = 8,515)
ANC one visit 2,400(28.19) 1,521(63.38) 879(36.63) <0.001
ANC two visit 2,154(25.30) 1,260(58.50) 894(42.50)
ANC three visit 1,727(20.28) 1,136(65.78) 591(34.22)
ANC 4 and above 2,234(26.24) 1,936(86.58) 298(13.44)
Pregnancy outcomes (n = 11,925)
Live births 11,593(97.22) 7,366(63.54) 4,227(36.46) 0.032
Abortion 178(1.49) 130(73.03) 48(26.97)
Still births 154(1.29) 97(62.99) 57(37.01)
Number of single and multiple tons (n = 11,593)
Single tons 11,447(98.74) 7,261(63.43) 4,186(36.57) 0.090
Multiple tons 146(1.26) 105(71.92) 41(28.08)
Gravidity (n = 7,263)
1 1,770(24.37) 1,366(77.18) 404(22.82) <0.001
2–4 2,926(40.29) 1,856(63.43) 1,070(36.57)
> = 5 2,567(35.34) 1,231(47.95) 1,336(52.05)
Slept in bed net (n = 11,925)
Yes 5,299(44.44) 3,232(60.99) 2,067(39.01) <0.001
No 3,575(29.98) 2,364(66.13) 1,211(33.87)
Do not have 3,051(25.58) 1,997(65.45) 1,054(34.55)
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Of the total deliveries, 7,535(63.19%) and 4,280 (35.89%) women delivered at health facilities and at home, respectively (Fig 1).

Fig 1. Place of delivery from 2009–2017 KA-HDSS sites of Mekelle University College of Health Science, Mekelle, Tigray Ethiopia.

Fig 1

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Of the total home deliveries, 97.87% were delivered by unskilled birth attendants. Of these 2,474(57.80%) deliveries were assisted by untrained traditional birth attendants, 390(9.11%) by health extension workers, 352 (8.22%) by mother herself and significant number of mothers (16.33%) were assisted by others (neighbors, grandmother, mother-in-law) (Fig 2).

Fig 2. Attendants of home delivery from 2009–2017 KA-HDSS sites, Mekelle University College of Health Science, Mekelle, Tigray Ethiopia.

Fig 2

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Magnitude and trends of skilled delivery and ANC attendance

The trend of skilled delivery over the study period (2009–2017) significantly increased from 17.30% (95% CI: 13.12% -22.17%) in 2009 to 95.85% (95% CI: 94.58%-96.89%) in 2017. The highest increment of skilled delivery was observed in the period 2011–2012 with a 33.35% increase followed by the period 2012–2013, which increased by 24.42% (Fig 3).

Fig 3. Trends of skilled delivery from 2009–2017 KA-HDSS sites of Mekelle University College of Health Science, Mekelle, Tigray Ethiopia.

Fig 3

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The trend of ANC attendance at least once in the study period (2009–2017) showed a significant change, increased from 48.44% (95% CI: 42.72%-54.21%) in 2009 to 94.7% (95% CI: 93.31–95.83%) in 2017. As shown in the Fig 4., ANC attendance 4+ continuously declined from 2009 to 2013 followed by inconsistent trend.

Fig 4. Trends of ANC attendance from of 2009–2017 KA-HDSS sites of Mekelle University College of Health Science, Mekelle, Tigray Ethiopia.

Fig 4

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Determinants of health facility deliveries

In the Bivariate analysis the variables residence, education, occupation, marital status, age at pregnancy, ANC attendance and number of ANC visits had statistically significant association with skilled delivery. The ANC attendance was not included in the multivariable binary logistic regression model due to multicollinearty with the number of ANC visits. Table 3 shows the determinants of skilled delivery among reproductive age women who gave birth during the period of 2009–2011 (when the skilled delivery rate was low) and 2014–2017 (when the skilled delivery rate was high). In the multivariable binary logistic regression model, the variables residence, education, occupation, marital status and number of ANC visits were found to be statistically significant contributors to skilled delivery during the period of 2014–2017. The Hosmer-Lemeshow test results confirmed that the model was a good fit for the data (X2(5) = 7.55, p-value = 0.1827). Keeping the effect of other predictors constant, unmarried women who gave birth during the period of high skilled delivery rate (2014 to 2017) were 2.18 (AOR: 2.18; 95% CI: 1.30–3.64) times more likely to have skilled delivery service compared to those who were married. In addition, women who had at least secondary, education were 2.10 times more likely to have skilled delivery service compared to those women with no education (AOR = 2.10, 95% CI: 1.18–3.74). Moreover, women with four or more ANC visits were 3.2 times more likely to have skilled delivery service than those having no ANC visits (AOR: 3.16; 95% CI: 2.33–4.28) (Table 3).

Table 3. Determinants of skilled delivery among reproductive age women who gave their recent birth from 2009 to 2011 and from 2014 to 2017 in KA-HDSS site, Tigray, Northern Ethiopia.

Variable 2009–2011 2014–2017
AOR SE P-value 95% CI AOR SE P-value 95% CI
Residence Rural 1.00 (reference category) 1.00 (reference category)
Urban 35.46 7.63 <0.001 23.26–54.06 27.58 27.66 0.001 3.86–196.97
Occupation Farmer 1.00 (reference category) 1.00 (reference category)
Merchant 2.25 0.98 0.061 0.97–5.26 0.60 0.20 0.121 0.31–1.15
Government employee 5.95 2.76 <0.001 2.40–14.78 0.79 0.52 0.719 0.22–2.87
Daily laborer 1.03 0.34 0.936 0.54–1.95 0.44 0.16 0.021 0.22–0.88
Housewife 0.71 0.19 0.181 0.42–1.18 0.55 0.15 0.027 0.33–0.94
Student 1.17 0.40 0.652 0.60–2.27 0.34 0.13 0.005 0.16–0.72
Unemployed 0.51 0.22 0.110 0.22–1.17 1.78 1.89 0.588 0.22–14.22
Other 1.29 0.43 0.448 0.67–2.48 0.30 0.10 <0.001 0.15–0.59
Marital Status Married 1.00 (reference category) 1.00 (reference category)
Unmarried 2.20 0.56 0.002 1.34–3.61 2.18 0.57 0.003 1.30–3.64
Others a 1.14 0.35 0.669 0.63–2.08 1.50 0.46 0.182 0.83–2.72
Educational Status Illiterate 1.00 (reference category) 1.00 (reference category)
Primary 1.70 0.29 0.002 1.22–2.36 1.63 0.24 0.001 1.23–2.17
Secondary and above 2.67 0.64 <0.001 1.67–4.27 2.10 0.62 0.011 1.18–3.74
ANC visits No ANC attendance 1.00 (reference category) 1.00 (reference category)
1–3 ANC visits 0.94 0.12 0.648 0.74–1.21 1.20 0.14 0.111 0.96–1.50
At least 4 ANC visits 1.61 0.34 0.024 1.07–2.45 3.16 0.49 <0.001 2.33–4.28
Previous pregnancy No 1.00 (reference category) 1.00 (reference category)
Yes 0.60 0.11 0.005 0.42–0.86 0.86 0.14 0.344 0.63–1.17
Age at pregnancy 15–19 1.00 (reference category) 1.00 (reference category)
20–24 1.82 0.51 0.032 1.05–3.14 0.84 0.27 0.589 0.46–1.57
25–29 2.40 0.72 0.004 1.33–4.33 1.11 0.38 0.758 0.57–2.19
30–34 3.06 0.94 <0.001 1.68–5.59 1.13 0.40 0.728 0.57–2.26
35–39 4.08 1.35 <0.001 2.14–7.81 0.95 0.34 0.895 0.48–1.92
40–44 3.97 1.52 <0.001 1.88–8.41 1.02 0.38 0.949 0.50–2.11
45–49 4.89 2.86 0.007 1.55–15.41 1.03 0.50 0.951 0.40–2.66
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Othersa: Widowed/divorced/separated, ANC: Antenatal Care, AOR: Adjusted odds ratio, SE: standard error

Discussion

The essential approach to improve maternal and neonatal health is increasing skilled delivery rate. Women giving birth at health institutions can prevent maternal and neonatal deaths through getting skilled birth attendance, drugs to address labour complications and referrals to more advanced health institutions [12]. This study aimed to assess the magnitude, trend and the factors that have contributed to the skilled delivery during the last nine years in KA-HDSS sites. Results showed that the skilled delivery rate in 2017 was 96% (95% CI: 94.85%-97.05%), which was higher than the studies done in Ethiopia [14–16]. This might be due to the fact that in the current study area many interventions were implemented at different times, which could have increased access to a health facility and community awareness. This study revealed that, the trend of skilled delivery was significantly increased over time. The rate of skilled deliveries among reproductive age women was increased by 83% from 2009 to 2017. This might be due to the improved health service promotion and health service delivery. In addition, the strong referral linkage of pregnant women from community to health facilities could also increase the rate of skilled delivery. In this study, 35.89% mothers delivered at home. Of these, 97.87% were assisted by unskilled birth attendants. These women might face potential complications such as bleeding, retained placenta, ruptured uterus and infection which could lead to death. In the present study, in 2017 about 4% of the women delivered at home, which was lower than the study conducted in Gurage zone, Ethiopia [23]. The possible reason could be in the current study area many interventions were implemented that could have increased access to health facility and community awareness on the benefits of healthcare services.

In the present study, the variables residence, marital status, educational status, occupation, and use of ANC service, were the determinants of the skilled delivery during the period of high skilled delivery rate (2014–2017). Primary education and secondary education and above were 1.63 and 2.1 times more likely to have skilled delivery service respectively as compared to those with no formal education. This finding was similar with the studies conducted in Ethiopia [20–22] where those who attended primary and secondary and above were more likely to utilize skilled delivery compared to those without formal education. This can be justified as education matters in knowledge acquisition and making a decision to utilize services. Women residing in urban areas increased the skilled delivery rate by 28 (AOR = 27.58; 95% CI: 3.86–196.97 as compared to rural residents. This is consistent with studies done in south and south west Ethiopia [21, 23]. This may be due to the fact that women residing in urban areas have more access to health information, access to nearby service and have more alternatives to health services compared to rural areas. Women with four or more ANC visits were 3.2 times more likely to have skilled delivery service than those having no ANC visits (AOR: 3.16; 95% CI: 2.33–4.28). These findings were similar to the previous studies conducted Ethiopia and Bangladesh [21, 23, 24]. This may be due to the educational packages given to ANC attendees that helped them to attend skilled delivery and postnatal care.

Conclusions

The findings of this study showed the skilled delivery rate for the period of 2014–2017, was high. The trend of skilled delivery over the study period (2009–2017) showed a significant increase. The socio-demographic variables and use of ANC services were found to be statistically significant contributors to skilled delivery. Therefore, we recommend a balanced health information and access to health care that could address the huge discrepancy in skilled delivery.

Acknowledgments

We would like to thank KA-HDSS office that provides permission with data access needed to conduct this research.

Abbreviations

KA-HDSS

Kilite-Awlaelo Health and Demographic Surveillance System

AOR

Adjusted odds ratio

CI

Confidence interval

ANC

antenatal care

SDG

Sustainable Development Goals

EDHS

Ethiopian Demographic and Health Surveys

MMR

Maternal Mortality Ratio

EPMM

ending preventable maternal mortality

IRB

Institutional Review Board

Data Availability

The data has potentially identifying information including name and households number. The data can be obtained from the institutional office Kilite-Awlaelo Health Demographic Surveillance System (KA-HDSS), College of Heath Science, Mekelle University, Email: ka.hdss.2011@gmail.com; Tel: +251914743841.

Funding Statement

The author(s) received no specific funding for this work.

References

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16 Apr 2021

PONE-D-21-07404

Magnitude, trends and determinants of skilled delivery from Kilite-Awlaelo Health Demographic Surveillance System, Northern Ethiopia, 2009- 2017

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Reviewer #1: No

**********

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Reviewer #1: I Don't Know

**********

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Reviewer #1: Yes

**********

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Reviewer #1: No

**********

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Reviewer #1: Access to care, and quality of the care provided at the facilities and the attending health care providers, are important factors determining pregnancy outcomes. Hence, this is an important issue to research and provide insight into how to improve the situation. The analysis and paper in its current form, however, do not add to the existing knowledge about factors that are associated with poor access to care and deliveries at health care facilities. Rather than trends the data could be analysed for various periods, say 2016, 2012, 2009 to identify the factors that were associated when the skilled delivery rates were low (in 2009) and factors that area associated when the skilled delivery rate has risen to above 90%. That might help identify strategies relevant for promoting skilled attendance at delivery for women who in 2020 still find it difficult to access health care facilities for delivery or decide to deliver at home for various socioeconomic, health system, geographic or cultural factors.

Abstract: The statements that “overall skilled delivery rate is 63.2%’ requires description/further explanation. Does it mean that the author added all the deliveries from 2009 to 2017 and 63.2% is the average across the years? If this is how the overall rate is calculated then it is unhelpful as what matters is the current rate of 96% and its comparison to the low rates a decade ago. An overall/average rate for all the deliveries across the years does not provide useful information.

Line 58-59: It is mentioned that the fundamental approach to improve maternal health is increasing skilled delivery. Access to skilled attendants at delivery is essential. However, it is important to consider the quality of care considering the recent research that points to poor outcomes despite high access. The data in this paper as well as a number of studies from around various developing countries inform that a majority of women is now delivered by the skilled attendants, and that a major contributory factor toward high maternal mortality is the poor quality of maternal health care. The quality of care is an increasingly fundamental concern and access to care and deliveries by skilled attendants need to be discussed within that context

Lines 67-69: Need to inform about the current MMR. At present 2011 MMR is presented. Since than access to skilled attendance has increased significantly. Hence, MMR o 2016 or 2017 is needed to be presented to contrast the 2009 and 2017 situation in terms of both access to skilled attendants at delivery and maternal mortality in Ethiopia.

Line 74-75: Not clear what is meant by “….respectively so the average skilled delivery rate of Ethiopia become 28% even if the health sector transformation plan of the country was set to be 90%”.

Line 92-101: Method that KA HDSS used needs to be presented in more detail, in order to better assess the methodology. Not clear what is meant by “retrospective open cohort study”.

METHOD: It seems over the years KA HDSS sample size increased from 14,455 households to 21,688 households. It is not described if 21,688 households included the same households or if every year the survey was conducted amongst a different set of households. If the survey is conducted amongst the same households there is need to discuss the potential impact of that research on health services utilisation by those households; respondents’ reflecting on health services access related questions in the survey might prompt for and improve healthcare seeking. Hence, there is a possibility that the respondents who take part in such repeated surveys act differently compared to the population at large. It is important to describe the methods of KA HDSS in more detail.

Lines 112-113: Some of the ‘births at home’ were conducted by skilled health care providers. If those deliveries are to be excluded then the study focus need to be ‘healthcare facility-based’ versus deliveries at homes.

Lines 148-149: Lack clarity, not clear what is meant by “…. the number of deliveries were 3,842(52.89%) observations had delivered one 148 times,2320(31.94%) two times, 966 (13.30%) three times,130(1.79%) four times and 5(0.07%) 49 five times”.

Lines 159-160: Lack clarity: “Based on their ANC visits, 8,515 of 11,925 (71.40%) of women had ANC visits at least one with a median time to visit was 2.5 times”.

Table 1/ 2: If data about ‘gravida’ is available it should be included and analysed.

Lines 177-178: Need to describe what is an ‘health extension worker’ (do they qualify as skilled attendants”).

Line 189-170: Need to explain what is meant by “overall skilled delivery rate”. The Figure 1 appears to be based on adding ALL deliveries across 9 years. Such averages are not helpful in defining the situation or trend. What matters is that in 2017 96% women delivered at the facilities.

Lines 194-195: Need clarity. “The trend of ANC attendance in the study period (2009-2017) showed a significant change, increased from 48.44% (95% CI: 42.72%-54.21%) in 2009 to 94.7% (95%CI: 93.31-95.83%) in 2017. One ANC or Four ANC?

Lines 193-207: ANC, HIV, malaria bed nets use are not the focus of this study. There are considered as independent variable for this study which attempts identifying the factors that are associated with accessing skilled birth attendants at health facilities. For this paper it is sufficient to inform if these were or were not associated with having delivery by a skilled attendants. Information on these variables per se is not relevant. For the same reasons, figures 3, 4, 5 are not needed.

DISCUSSION needs to be strengthened. At present many of the results are repeated in the discussion, and the discussion does not discuss in depth to add to the existing knowledge about factors that determine access to skilled attendants at delivery/births at health facilities.

If the data is reanalysed in light of the suggestion above, the discussion would need to be aligned with the revised analysis and results.

There are significant difference noted between access to skilled attendants/ delivery at facilities between urban and rural areas. This finding needs to be discussed within the context of urban and rural MMR in Ethiopia with reflections whether better access in urban areas translates into better pregnancy outcomes and lower maternal mortality ration.

REFERENCES needs to be correctly formatted in line with the Journal requirement.

ENGLISH LANGUAGE editing is required. Some examples of statements that lack clarity include:

Line 50: ‘The skilled attendant is an accredited health professional of midwives, doctors, and nurses with midwifery and life-saving skills’. What is meant by ‘an accredited health professional of midwives……’?.

line 219-220: “Like wisely, single women who gave their recent birth from 2009 –2017 in the study setting were 2.13 (AOR: 2.13; 95% CI: 1.71 –2.65) times more likely to have skilled delivery

Line 255: “….higher than the studies done in Ethiopia [16-19].This might be related to the fact that in the current study area many interventional have been implemented…”

Line 276: “….. that women residing in urban areas are more accessible to health information, access…”

**********

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PLoS One. 2021 Sep 9;16(9):e0254146. doi: 10.1371/journal.pone.0254146.r002

Author response to Decision Letter 0

28 May 2021

Manuscript ID: PONE-D-21-07404.

Magnitude, trends and determinants of skilled delivery from Kilite-Awlaelo Health Demographic Surveillance System, Northern Ethiopia, 2009- 2017

Authors: Abebe et al.

Dear Professor Frank T. Spradley,

First of all we would like to thank you very much for the chance you gave us to revise the manuscript and we really appreciate the comments and suggestions.

Based on the instructions provided in the journal's website and your email on April 16, 2021, we have revised the manuscript along the line of all comments made by the academic editor and reviewer.

Appended to this letter is our point-by-point response to the comments raised by the academic editor and reviewer. Essentially, we agreed with almost all the comments, and we would like to express our sincere thanks to the referee for identifying areas of our manuscript that needed modifications or corrections. We would also like to thank you for allowing us to re-submit a revised version of the manuscript.

We hope that the revised manuscript is acceptable for publication in PLOS ONE.

Sincerely Yours,

Haftom Temesgen Abebe

Responses to academic editor comments

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at

https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and

https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf

Response: We have revised the manuscript according the PLOS ONE’s style. (see the revised manuscript)

2. We suggest you thoroughly copyedit your manuscript for language usage, spelling, and grammar. If you do not know anyone who can help you do this, you may wish to consider employing a professional scientific editing service.

Whilst you may use any professional scientific editing service of your choice, PLOS has partnered with both American Journal Experts (AJE) and Editage to provide discounted services to PLOS authors. Both organizations have experience helping authors meet PLOS guidelines and can provide language editing, translation, manuscript formatting, and figure formatting to ensure your manuscript meets our submission guidelines. To take advantage of our partnership with AJE, visit the AJE website (http://learn.aje.com/plos/) for a 15% discount off AJE services. To take advantage of our partnership with Editage, visit the Editage website (www.editage.com) and enter referral code PLOSEDIT for a 15% discount off Editage services. If the PLOS editorial team finds any language issues in text that either AJE or Editage has edited, the service provider will re-edit the text for free.

Upon resubmission, please provide the following:

• The name of the colleague or the details of the professional service that edited your manuscript

• A copy of your manuscript showing your changes by either highlighting them or using track changes (uploaded as a *supporting information* file)

• A clean copy of the edited manuscript (uploaded as the new *manuscript* file)

Response: Thank you for the suggestions. Our paper is edited by Dr Carmer C. Robles (PhD), email: chenyta08@yahoo.com

3. We note that you have indicated that data from this study are available upon request. PLOS only allows data to be available upon request if there are legal or ethical restrictions on sharing data publicly. For information on unacceptable data access restrictions, please see http://journals.plos.org/plosone/s/data-availability#loc-unacceptable-data-access-restrictions.

In your revised cover letter, please address the following prompts:

a) If there are ethical or legal restrictions on sharing a de-identified data set, please explain them in detail (e.g., data contain potentially identifying or sensitive patient information) and who has imposed them (e.g., an ethics committee). Please also provide contact information for a data access committee, ethics committee, or other institutional body to which data requests may be sent.

b) If there are no restrictions, please upload the minimal anonymized data set necessary to replicate your study findings as either Supporting Information files or to a stable, public repository and provide us with the relevant URLs, DOIs, or accession numbers. Please see http://www.bmj.com/content/340/bmj.c181.long for guidelines on how to de-identify and prepare clinical data for publication. For a list of acceptable repositories, please see http://journals.plos.org/plosone/s/data-availability#loc-recommended-repositories.

We will update your Data Availability statement on your behalf to reflect the information you provide.

Response: The data has potentially identifying information including name and households number. The data can be obtained from the institutional office Kilite-Awlaelo Health Demographic Surveillance System (KA-HDSS), College of Heath Science, Mekelle University, Email: ka.hdss.2011@gmail.com; Tel: +251914743841

4. Please amend the manuscript submission data (via Edit Submission) to include author Haftom Temesgen.

Response: Done, we have now corrected this.

5. Please amend your authorship list in your manuscript file to include author Haftom Abebe.

Response: Done.

6. Please amend either the abstract on the online submission form (via Edit Submission) or the abstract in the manuscript so that they are identical.

Response: Done.

7. Your ethics statement should only appear in the Methods section of your manuscript. If your ethics statement is written in any section besides the Methods, please delete it from any other section.

Response: Done. Please see the revised paper.

Responses to reviewers’ comments

First of all we would like to thank you very much for the comments.

Reviewer1:

Access to care, and quality of the care provided at the facilities and the attending health care providers, are important factors determining pregnancy outcomes. Hence, this is an important issue to research and provide insight into how to improve the situation. The analysis and paper in its current form, however, do not add to the existing knowledge about factors that are associated with poor access to care and deliveries at health care facilities. Rather than trends the data could be analysed for various periods, say 2016, 2012, 2009 to identify the factors that were associated when the skilled delivery rates were low (in 2009) and factors that area associated when the skilled delivery rate has risen to above 90%. That might help identify strategies relevant for promoting skilled attendance at delivery for women who in 2020 still find it difficult to access health care facilities for delivery or decide to deliver at home for various socioeconomic, health system, geographic or cultural factors.

Response: Thank you very much for the suggestion. We have now identify the factors associated with the skilled delivery for the period of low skilled delivery rates (2009-2011) and factors that were associated with the outcome for the period of high skilled delivery rate(2014-2017) (Table 3).

Note that because of zero cells for most of the variables we could not analysed separately for various periods (2009, 2017), instead we analysed for 2009-2011 when the skilled delivery rate was low and for the period 2014-2017 when the skilled delivery rates was above 82%. Please see the revised manuscript Table 3.

Abstract: The statements that “overall skilled delivery rate is 63.2%’ requires description/further explanation. Does it mean that the author added all the deliveries from 2009 to 2017 and 63.2% is the average across the years? If this is how the overall rate is calculated then it is unhelpful as what matters is the current rate of 96% and its comparison to the low rates a decade ago. An overall/average rate for all the deliveries across the years does not provide useful information.

Response: Yes, the overall skilled delivery rate is the average across the years. We have now removed this. Please see the revised paper

Line 58-59: It is mentioned that the fundamental approach to improve maternal health is increasing skilled delivery. Access to skilled attendants at delivery is essential. However, it is important to consider the quality of care considering the recent research that points to poor outcomes despite high access. The data in this paper as well as a number of studies from around various developing countries inform that a majority of women is now delivered by the skilled attendants, and that a major contributory factor toward high maternal mortality is the poor quality of maternal health care. The quality of care is an increasingly fundamental concern and access to care and deliveries by skilled attendants need to be discussed within that context

Response: Thank you for the comments. We have now included. Please see the revised.

Lines 67-69: Need to inform about the current MMR. At present 2011 MMR is presented. Since than access to skilled attendance has increased significantly. Hence, MMR o 2016 or 2017 is needed to be presented to contrast the 2009 and 2017 situation in terms of both access to skilled attendants at delivery and maternal mortality in Ethiopia.

Response: Thank you for the Comments. We have now included MMR for 2016. See the revised paper.

Line 74-75: Not clear what is meant by “….respectively so the average skilled delivery rate of Ethiopia become 28% even if the health sector transformation plan of the country was set to be 90%”.

Response: We agree and we have now revised this statement. Please see the revised manuscript.

Line 92-101: Method that KA HDSS used needs to be presented in more detail, in order to better assess the methodology. Not clear what is meant by “retrospective open cohort study”.

Response: Thank you again for the comments. We have now described this in detail. Please see the revised.

METHOD: It seems over the years KA HDSS sample size increased from 14,455 households to 21,688 households. It is not described if 21,688 households included the same households or if every year the survey was conducted amongst a different set of households. If the survey is conducted amongst the same households there is need to discuss the potential impact of that research on health services utilisation by those households; respondents’ reflecting on health services access related questions in the survey might prompt for and improve healthcare seeking. Hence, there is a possibility that the respondents who take part in such repeated surveys act differently compared to the population at large. It is important to describe the methods of KA HDSS in more detail.

Response: The 21,688 households include existing households (14, 455 HHs) and newly households that has been included later in 2016. We have now described this in more detail. Please see the revised.

Lines 112-113: Some of the ‘births at home’ were conducted by skilled health care providers. If those deliveries are to be excluded then the study focus need to be ‘healthcare facility-based’ versus deliveries at homes.

Response: Thank you for the comments. Indeed some of the births at home were delivered by skilled birth attendants. We have now corrected this, i.e., the outcome was dichotomizes as one if a women gave birth by skilled birth attendants and 0 otherwise. Accordingly we have reanalysed and modified our results (Table 1, Table 2 and Figure 3). Please see the revised paper.

Lines 148-149: Lack clarity, not clear what is meant by “…. the number of deliveries were 3,842(52.89%) observations had delivered one 148 times,2320(31.94%) two times, 966 (13.30%) three times,130(1.79%) four times and 5(0.07%) five times”.

Response: Comments accepted. We have now corrected. Please see the revised manuscript.

Lines 159-160: Lack clarity: “Based on their ANC visits, 8,515 of 11,925 (71.40%) of women had ANC visits at least one with a median time to visit was 2.5 times”.

Response: We have now revised and corrected the statement.

Table 1/ 2: If data about ‘gravida’ is available it should be included and analysed.

Response: Thank you for the suggestion. We have now included this in Table 2. Please see in the revised paper.

Lines 177-178: Need to describe what is an ‘health extension worker’ (do they qualify as skilled attendants”).

Response: No they don’t qualify as skilled birth attendants. As defined by WHO skilled birth attendant is a health professional such as midwife, doctor or nurses who has been educated and trained to proficiency in the skills needed to manage women during normal (uncomplicated) childbirth and the immediate postnatal period as well as in the identification.

We have now described this. Please see the revised paper.

Line 189-170: Need to explain what is meant by “overall skilled delivery rate”. The Figure 1 appears to be based on adding ALL deliveries across 9 years. Such averages are not helpful in defining the situation or trend. What matters is that in 2017 96% women delivered at the facilities.

Response: Yes, the overall skilled delivery rate is the average across the years. We agree and we have now removed this. Please the revised paper

Lines 194-195: Need clarity. “The trend of ANC attendance in the study period (2009-2017) showed a significant change, increased from 48.44% (95% CI: 42.72%-54.21%) in 2009 to 94.7% (95%CI: 93.31-95.83%) in 2017. One ANC or Four ANC?

Response: The comment is accepted. This trend is for ANC attendance at least once. We have described this. Please see the revised paper.

Lines 193-207: ANC, HIV, malaria bed nets use are not the focus of this study. There are considered as independent variable for this study which attempts identifying the factors that are associated with accessing skilled birth attendants at health facilities. For this paper it is sufficient to inform if these were or were not associated with having delivery by a skilled attendants. Information on these variables per se is not relevant. For the same reasons, figures 3, 4, 5 are not needed.

Response: We agree and we have now dropped the figures (4 and 5). Please see the revised manuscript.

DISCUSSION needs to be strengthened. At present many of the results are repeated in the discussion, and the discussion does not discuss in depth to add to the existing knowledge about factors that determine access to skilled attendants at delivery/births at health facilities.

Response: We have now revised the discussion. Please see the revised paper.

If the data is reanalysed in light of the suggestion above, the discussion would need to be aligned with the revised analysis and results.

Response: We have revised the discussion based on the suggestions. Please see the revised paper.

There are significant difference noted between access to skilled attendants/ delivery at facilities between urban and rural areas. This finding needs to be discussed within the context of urban and rural MMR in Ethiopia with reflections whether better access in urban areas translates into better pregnancy outcomes and lower maternal mortality ration.

Response: Comment accepted. We have now done this. Please see the revised manuscript.

REFERENCES needs to be correctly formatted in line with the Journal requirement.

Response: We have the corrected the reference formatted in line with the Journal requirement.

ENGLISH LANGUAGE editing is required. Some examples of statements that lack clarity include:

Line 50: ‘The skilled attendant is an accredited health professional of midwives, doctors, and nurses with midwifery and life-saving skills’. What is meant by ‘an accredited health professional of midwives……’?.

line 219-220: “Like wisely, single women who gave their recent birth from 2009 –2017 in the study setting were 2.13 (AOR: 2.13; 95% CI: 1.71 –2.65) times more likely to have skilled delivery

Line 255: “….higher than the studies done in Ethiopia [16-19].This might be related to the fact that in the current study area many interventional have been implemented…”

Line 276: “….. that women residing in urban areas are more accessible to health information, access…”

Response: Thank you again. We have now edited the English language by colleague Dr Carmer C. Robles (PhD), email: chenyta08@yahoo.com. Please see the revised paper.

Attachment

Submitted filename: Responses to reviewer and editor.doc

Click here for additional data file. (59.5KB, doc)

Decision Letter 1

Frank T Spradley

21 Jun 2021

Magnitude, trends and determinants of skilled delivery from Kilite-Awlaelo Health Demographic Surveillance System, Northern Ethiopia, 2009- 2017

PONE-D-21-07404R1

Dear Dr. Abebe,

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.

An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

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,

Frank T. Spradley

Academic Editor

PLOS ONE

Acceptance letter

Frank T Spradley

25 Jun 2021

PONE-D-21-07404R1

Magnitude, trends and determinants of skilled delivery from Kilite-Awlaelo Health Demographic Surveillance System, Northern Ethiopia, 2009- 2017

Dear Dr. Abebe:

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

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 plosone@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. Frank T. Spradley

Academic Editor

PLOS ONE

Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    Attachment

    Submitted filename: Responses to reviewer and editor.doc

    Click here for additional data file. (59.5KB, doc)

    Data Availability Statement

    The data has potentially identifying information including name and households number. The data can be obtained from the institutional office Kilite-Awlaelo Health Demographic Surveillance System (KA-HDSS), College of Heath Science, Mekelle University, Email: ka.hdss.2011@gmail.com; Tel: +251914743841.

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