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Research Article
Revised

Factors associated with health facility delivery in Kitui County: a cross sectional study

[version 3; peer review: 1 approved, 1 approved with reservations, 2 not approved]
PUBLISHED 18 Jan 2024
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Abstract

Background

High maternal mortality rate is a major public health concern in developing countries. Skilled birth delivery is key to reducing maternal mortality, yet health facility delivery (skilled birth delvery) remains low in Kitui County, Kenya. Our study estimated prevalence of unskilled delivery and identified factors associated with health facility delivery in Kitui County.

Methods

A cross-sectional study was conducted December 2017-February 2018. 245 women from five administrative wards were interviewed. A structured questionnaire was used to collect data. Variables that had p value ≤0.05 in bivariate analysis were included in multivariate regression model to assess for confounders. Variables with a p value of ≤0.05 in multivariate analysis were considered statistically significant at 95% CI.

Results

We interviewed 245 (240 analyzed) women from the five wards; the majority were 16-25 years age group (45.5%; 110/240). Mean age was 27±6.6 years. Prevalence of health facility delivery was 50.4%. Distance from a health facility, number of children in a household, occupation of the respondent’s partner, number of antenatal clinic (ANC) visits and means of transport were significant factors for not delivering in a health facility. On multivariate analysis, women who lived ≥5km from health facility were less likely to deliver in a health facility (AOR =0.36; 95% CI 0.15- 0.86). Women who attended ≥ 4 ANC visits were 4 times more likely to deliver in a health facility (95% CI 2.01-8.79).

Conclusions

More than half of the respondents delivered in a health facility. A long distance (over5kms radius) from the health facility is a hindrance to accessing ANC services. Inadequate ANC visits was associated with home delivery. Improving accessibility of health care services and health education on family planning would increase delivery at a health facility. We recommend Kitui County introduce five satellite clinics/ambulatory services so that expectant women can access maternal services easily.

Keywords

Home delivery, Health facility delivery, skilled birth delivery, delivery practices, Kitui

Revised Amendments from Version 2

The issue of selection biasness is ruled out by how participants were identified i.e. the first 5 maternal child care clients were identified on a first come -first serve principle that operates within the health care settings. Therefore, the use of mean and standard deviations was considered appropriate.

See the authors' detailed response to the review by Ferry Efendi
See the authors' detailed response to the review by Danish Ahmad

Introduction

Globally, the maternal mortality rate has continued to increase leading to failure by countries to achieve the Millennium Development Goals (MDGs) that were set in year 1990 to 20151. This made it impossible to achieve the MDG 52 that aimed to reduce maternal and neonatal deaths (now Sustainable Development Goal (SDG) 3). However, maternal deaths have reduced from 546,000 in 1990 to 358,000 in 2015 in sub Sahara region representing a 34% reduction. Between 2016 and 2030, as part of the SDGs, the target is to reduce the global maternal mortality ratio to less than 70 per 100 000 live births3. In order to achieve, universal health care has been recognized as one of four pillars of government policy and is therefore receiving support from many quarters.

According to Safe Motherhood Initiative (SMI) introduced by World Health Organization (WHO), hospital deliveries were fewer than home deliveries in many regions of sub-Saharan Africa (SSA). The reason for this is that the initiative lacks a clear, concise realistic strategy4. As a result, a high number of still births (3.2 million), 4 million neonatal deaths and more than half a million maternal deaths, continue to occur. Most of these deaths are preventable4, and when skilled health personnel provide delivery services within health facilities to pregnant women, maternal and neonatal health outcomes improve5.

In Kenya, skilled birth attendance (44%). has remained far below the international target of 90% Skilled birth attendance during delivery is a benchmark indicator for safe motherhood6. Delivery by a skilled birth attendant reduces chances of maternal complications. A study by Nyongesa et al. found that the gender of a service provider, cost, number of antenatal visits and education level were strongly associated with client’s intention to deliver with a skilled birth attendant at delivery7.

In Kitui County, Kenya, skilled birth attendance has equally remained very low. Moreover, Mwingi North Sub county had recorded low number of deliveries in the health facilities. The district health information system (DHIS2) reported 1472 normal hospital deliveries in 2015 were 1472, 1594 in 2016, and 1194 deliveires in 20178.

Even though delivery by skilled birth attendants have remained low, the immunization coverage at the country and the county level have remained above the national government rate, This means that immunization coverage is not proportional to the number of skilled birth attendants. According to the Kenya health information system (KHIS), the number of Bacillus Calmette Guillen (BCG) antigen doses administered in Mwingi North Sub county in 2017 was 3268, while the number of deliveries recorded by skilled birth attendants was 11548. This means that over 65% of babies were delivered at home without the help of a skilled birth attendant, as BCG vaccines are administered within 6 weeks of birth.

Improving maternal delivery care is an essential element of attaining improved maternal health. In order to achieve improved maternal health, information about the rates and trends in maternal mortality is essential for resource mobilization, monitoring and evaluation of progress towards the SDGs. However, for this to be attained, maternal health programs should be based on quality evidence. Therefore, this cross-sectional study aimed to identify factors affecting health facility deliveries in Mwingi North Sub county, Kitui county. Kenya.

Methods

Study setting

The study was carried out in five administrative wards of Mwingi North Sub county, which has a catchment population of 160,938 persons. Within the Sub county, there are two Sub county hospitals, six health centres, 20 dispensaries, two private nursing homes, and one level 4 hospital. Cadres of staff include medical officers (n=2), pharmacists (1), nursing officers (60), clinical officers (14), public health officers (10), nutritionists (2), and medical laboratory technologists (13). Approximately 34,800 women of reproductive age reside in the Sub county (KDHS, 2014).

Study population

The study population included women of reproductive age (14–49 years) who had delivered within the preceding two years (1st January 2016 to 31st January 2018). Women who were below the age of 18 years and were not accompanied by a guardian or a parent, those with psychiatric problems and very ill women were excluded from the study.

Women who were attending clinics for routine appointments and who met the inclusion criteria were requested to spare about 15 minutes to participate in the interview. The respondents were picked on first come - first serve basis, whereby the first 5 attendees of maternal child health services were picked every day until the proportionate sample for each health facility was achieved.

Sample size and sampling technique

Sample size was determined using proportion of home deliveries to proportion of hospital deliveries. This data was collected from DHIS; home deliveries (80%) and in hospitals (20%) in the study area. The standard error was set at 5% and Z score value of 1.96 for 95% Confidence Interval (CI). Multistage and proportionate sampling techniques were applied. The sample size required was 245. Purposively, Mwingi North Sub county was selected among the eight Sub Counties of Kitui County. Proportionate sampling was done among the five wards of Mwingi North Sub County according to their catchment population and the number of health facility deliveries reported.

Data collection and instruments

A structured questionnaire was administered by five research assistants between 1st December 2017 and 31st January 2018. The questionnaire was administered face to face at the health facilities as the respondents sought maternal child health services. The questionnaire had the following variables:- demographic information, social economic and facility related questions (see Extended data9).

Data analysis

Study variables were classified as either dependent (outcome) variables or independent (exposure) variables. These included age, marital status, level of education, parity, occupation, number of people living in a house and distance from health facilities,

We carried out descriptive statistics, Chi square test and calculated odds ratios.

The data was collected using printed paper questionnaire, which was later entered into Microsoft Excel 2010. Analysis was based on the specific objectives of identifying factors affecting delivery, respondents’ characteristics and calculation of prevalence of skilled birth attendant. Bivariate and multivariate models were applied using binary logistic regression to assess any relationship between independent variables and health facility delivery. Data was analyzed using Statistical Package for Social Sciences (SPSS) v.25.

We calculated crude and adjusted odds ratios to ascertain if there was any association between the outcome and predictor variables. The significance of these factors was determined using 95% CI. Independent variables found to be significant with p value less than 0.05 on bivariate analysis were included in a multivariate logistic regression model to control for any potential confounding variables.

Ethical considerations

Study tools and protocol were approved by the Meru University of Science and Technology Ethical Review Committee (approval number: MIRERC/923/2017), while permission to carry out the study was granted by County government of Kitui.Respondents provided both written and verbal informed consents following introduction and explanation on the purpose of study being done. Those who could write, appended a signature to the consent form while others left their thumb prints on the form. They were informed about their right to interrupt the interview at any time or even decline to be interviewed without any future prejudice or facing consequence.

Results

Demographic characteristics

We interviewed a total of 245 women; the data from 240 women were analyzed as 5 records were removed from analysis as most variables from these individuals were not captured.

The mean age of the respondents was 27.6 years (± standard deviation (SD) 6.5). The mean age of respondents reporting a previous health facility delivery was 27.4±6.6, while respondents reporting previous home deliveries had a mean age of 27.5±6.5. Most respondents were in the age group of 16–25 years (110; 45.8%), followed by the age groups 26–35 years (94; 39.2%) and >35 years (28; 11.7%). A small proportion of respondents did not know their age (8; 3.3%).

Among respondents reporting hospital deliveries, Kyuso ward had majority of deliveries (91; 37.9%) while Tharaka ward had only 32 (13.3%) (chi2=12.8, df=4, p=0.01). Overall, Ngomeni ward had the highest proportion of home deliveries (22; 9.2%) Table 1a.

Table 1a. Social demographic characteristics of women of reproductive age in Mwingi North Sub County in 2018.

VariablesCategoriesDelivery location, n (%)P value
Health facilityHome
Age, years15–1910 (4.3)9 (3.9)0.99
20–2439 (16.8)37 (16.0)
25–2926 (11.3)24 (10.4)
30–3428 (12.1)30 (12.9)
35–4914 (6.1)14 (6.1)
Mean age27.4±6.627.5± 6.5
Marital statusDivorced2 (0.8)4 (1.7)0.36
Married89 (37.1)92 (38.3)
Single28 (11.7)23 (9.6)
Widow2 (0.8)0 (0)
OccupationBusiness26 (10.8)14 (5.8)0.01
Casual Jobs19 (7.9)12 (5.0)
Farming/Livestock22 (9.2)40 (16.7)
Formal Jobs3 (1.3)0
Housewife51 (21.3)53 (22.1)
EducationAdult education0 (0)3 (1.3)0.33
College/University11 (4.6)7 (2.9)
No Education5 (2.1)5 (2.1)
Primary72 (30.0)77 (32.1)
Secondary33 (13.8)27 (11.3)
WardKyuso49 (20.4)42 (17.5)0.01
Mumoni16 (6.6)17 (7)
Ngomeni18 (7.5)26 (10.8)
Tharaka10 (4.2)22 (9.2)
Tseikuru28 (11.7)12 (5)
Attended ANCAttended71 (29.6)31 (12.9)0.001
Not Attended50 (20.8)87 (36.25)
No of ANCLess than 451 (21.3)88 (36.7)0.0001
attended4 or More70 (29.2)31 (12.9)
Means of transportAmbulance55 (22.9)59 (24.6)0.02
Own transport33 (13.8)16 (6.7)
Public transport33 (13.8)44 (18.3)
Distance<5km51 (21.3)21 (8.8)0.00001
6 to 10 km41 (17.1)45 (18.8)
Above 10 km29 (12.1)53 (22.1)

In terms of education level, most of the women (149; 62.7%) were primary school leavers. Out these women, 32.1% (77) delivered at home. Very few (10; 4.2%) of the respondents did not have any form of education. There was no significant association between level of education and delivery in a health facility (chi2=4.64, df=4, p=0.33).

Socio-demographic factors associated with health facility delivery

The majority of respondents were housewives, for both deliveries in health facilities and at home (51; 21.3% and 53; 22.1%, respectively). All (3; 100%) respondent who had formal jobs delivered in a health facility, while the majority of women who were farmers/livestock keepers (40; 16.7%) delivered at home and 22 (9.2%) delivered in a health facility.

On bivariate analysis, occupation of the mother (chi2=13.42, df=4, p=0.01), partner occupation (chi2=18.7, df=4, p=0.001), distance from health facility (chi2=19.7, df=2, p=0.0001) and residence (chi2=12.8, df=4, p=0.01) were factors found to be significantly associated with health facility delivery in Mwingi north Sub county (Table 1a).

On multivariate analysis, women who lived >5 kilometers away from health facilities were 38% less likely to deliver in a health facility (adjusted odds ratio (AOR) = 0.38, 95% CI 0.15-0.86). Partner occupation was also significant for delivery in a health facility (AOR = 0.67, 95% CI 0.26–1.71) (Table 2).

Reproductive health-related determinants for place of delivery

Regarding the number of antenatal clinic (ANC) visits, 58% (139) of respondents attended less than four visits. Among these, 21.3% delivered in a health facility while the rest delivered in their homes. The majority of those who attended more than four ANC visits (70; 29.2%) delivered in a health facility as opposed to 12.9% (31) who delivered in their homes. When we carried out bivariate analysis, number of ANC visits was significant for giving birth in a health facility (chi2=23.6, df=1, p=0.001).

Almost a quarter of the respondents (65; 21.1%) had a parity of 1+0, among them 64.6% (42) delivered in a health facility while the rest delivered in their homes. There were 31 respondents who had a parity of >5 (12.9%), of these the majority (24; 10%) delivered in their homes.

Regarding family size (number of children) in household most of the respondents 48.8% (117) had 1-2 children. Of these 64.9% (76) delivered at a health facility while the rest delivered in their homes, however respondents who had more than 7 children were few 6.7%(16) of which 81.1% (13) delivered in their homes Chi2=21.6,df=3, pvalue=0.00007 (Table 2).

In a multivariate model, four or more ANC visits (AOR=2.914, 95% CI 1.105-7.682), parity of the woman (AOR=0.12, 95% CI 0.01-3.44) and the number of children in the homestead (AOR=1.96, 95% CI 0.06-35.02) did not significantly influence place of delivery (Table 2).

Facility and cultural-related factors affecting delivery in a health facility

Most of the respondents (86; 35.9%) lived approximately 6 to 10 km away from a health facility. Among these 18.8% (45) delivered at home, while only 17.1% (41) delivered in a health facility. Very few respondents lived a distance less than 5km from a health facility (71; 30.1%) (chi2=19.7, df=2, p=0.0001).

Distance from a nearby health institution, means of transport, cost of transport and presence of traditional practices were factors that were statistically significantly determined place of delivery (Table 1b).

Table 1b. Social demographic characteristics of women of reproductive age in Mwingi North Sub County in 2018.

VariableCategoryDelivery location, n (%)
Health facilityHomePvalue
Parity1+042 (17.5)23 (9.6)0.001
2+033 (13.8)18 (7.5)
3+022 (9.2)29 (12.1)
4+015 (6.3)25 (10.4)
5+02 (0.8)0 (0)
>5+07 (2.9)24 (10.0)
Partner occupationBusiness36 (15.0)21 (8.8)0.001
Casual Jobs9 (3.8)9 (3.8)
Farming/Livestock31 (12.9)58 (24.2)
Formal Jobs11 (4.6)2 (0.8)
Missing34 (14.1)29 (12.1)
Cost of transportAffordable64 (26.7)43 (17.9)0.001
Not affordable56 (23.3)70 (29.2)
Don't know1 (0.42)6 (2.5)
No of children1 to 276 (31.7)41 (17.1)7.60E-05
3 to 431 (12.9)47 (19.6)
5 to 611 (4.6)18 (7.5)
>73 (1.3)13 (5.4)
People living in the household0 to 320 (8.3)10 (4.2)0.079
4 to 550 (20.8)41 (17.1)
6 to 731 (12.9)39 (16.3)
>820 (8.3)29 (12.1)
Any practices that hinder delivery
At health facility delivery
Present94 (39.2)27 (11.3)0.03
Absent106 (44.2)13 (5.4)

Table 2. Factors associated with delivery in health facilities among women of reproductive age in Mwingi North Sub county in 2018.

VariablesCategoriesDelivery location,
n (%)
Crude OR (95%CI)Adjusted OR
(95%CI)
Health
facility
Home
Parity 1+042 (17.5)23 (9.6)11
2+033 (13.8)18 (7.5)1 (4.6e-01 - 2.1)0.84 (0.28-2.52)
3+022 (9.2)29 (12.1)0.4 (1.9e-01- 0.87) 0.12 (0.01-3.44)
4+015 (6.3)25 (10.4)0.33 (1.42e-01 0.7) 0.07 (0.00-2.60)
>5+07 (2.9)24 (10.0)0.16 (5.61e-02 - 0.41) 0.05 (0.01-2.60)
Partner occupationBusiness36 (15.0)21 (8.8)11
Casual Jobs9 (3.8)9 (3.8)0.583 (0.197- 1.713)0.42 (0.10-1.73)
Farming/Livestock31 (12.9)58 (24.2)0.31 (0.15- 0.62) 0.67 (0.26-1.71)
Formal Jobs11 (4.6)2 (0.8)3.21 (0.76-22.04)0.49 (0.07-4.89)
Missing34 (14.1)29 (12.1)0.684 (0.33- 1.43)0.52 (0.15-1.67)
Number of children1 to 276 (31.7)41 (17.1)11
3 to 431 (12.9)47 (19.6)0.35 (0.19-0.64) 1.96 (0.06-35.02)
5 to 611 (4.6)18 (7.5)0.33 (0.14 -0.75) 5.16 (0.11-18.71)
7 or more3 (1.3)13 (5.4)0.124 (0.027-0.412) 2.81 (0.04-125)
Practices that hinder delivery
in a health facility delivery
Absent106 (44.2)13 (5.4)11
Present94 (39.2)27 (11.3)2.34 (1.16 -4.93) 1.92 (0.75-5.13)
Means of transportAmbulance55 (22.9)59 (24.6)11
Own transport33 (13.8)16 (6.7)2.21 (1.11-4.54) 4.20 (1.5-12.16)
Public transport33 (13.8)44 (18.3)0.80 (0.45-1.44)0.9 (0.42-1.94)
Distance<5km51 (21.3)21 (8.8)11
6 to 10 km41 (17.1)45 (18.8)0.37 (0.19- 0.72) 0.36 (0.15-0.86)
Above 10 km29 (12.1)53 (22.1)0.22 (0.11-0.44) 0.32 (0.13-0.74)

In a multivariate model, only distance that was associated factor for delivery in a health facility. Those who lived over 5km from a health facility were less likely to deliver in a health facility (AOR=0.37, 95% CI 0.19-0.72), presence of traditional practice (AOR=0.36, 95% CI 0.15-0.86) and means of transport (AOR=0.001, 95% CI 2.38-9.56). Those who used an ambulance on referral were more likely to deliver in a health facility than those who used other means of transport (Crude odds ratio (COR)=2.21, CI 95% 1.11–4.54) (Table 2).

Discussion

The percentage of women who delivered through the help of a skilled birth attendant is one indicator in meeting MDG 5 (now SDG3 – ensuring good healthy lives and promote wellbeing for all ages). In most countries where health professionals attend more than 80% of deliveries, maternal mortality rate is usually below 200 per 100,000 live births.

In Kenya, delivery by skilled birth attendants (health professionals) is available at very few births5. This study therefore considered factors affecting delivery in a health facility. The study has shown that that only 50.4% of the respondents had a delivery conducted by a skilled delivery attendant. Our results are slightly different from those from KDHS, whereby statistics for skilled attendants were 44% in Kenya.

Our study demonstrated that there is no significant relationship between age and delivery in a health facility. However, other studies, e.g. a study by Mrisho et al.10 in Tanzania, showed that a higher percentage of younger women deliver at health facilities in contrast to older women who often choose to deliver at home. A study by Bhattacharyaya et al. on factors associated with preference of a health facility delivery indicated that older women preferred health facility delivery as opposed to younger women11. The reason given for this discrepancy according to studies in Zambia and Tanzania was that younger women were inexperienced and more afraid of birth complications than older women.

The present study showed that attendance of >4 ANC visits influenced the place of delivery. This study agrees with a study that indicated that women who attended >4 ANC visits were likely to deliver in a health facility than those who did less visits11. In addition, the study by Bhattacharyya et al. indicated that marital status had little influence on the attendance of ANC during the mother’s last pregnancy and consequently on delivery in a health facility; in this study, single and married women mostly delivered either at home or at a government health facility. A study conducted in Myanmar12 showed similar findings. In this study, the majority of divorced women delivered at home whereas widowed women delivered at either a private or government health facility. Women who make more than 4 ANC visits may have bad obstetric history or perhaps have started ANC visits at earliest gestation12.

In our study, the number of children (parity) had a negative impact on delivery in a hospital. We found that women with higher parity and having more than two children in the family were more likely to deliver in their homes than their counterparts with low parity and one or two children. These study findings are similar to a study in Myanmar that indicated that women who have given birth more than once are less likely to seek maternal care at a health facility because they feel they can manage the birthing process without the assistance of a health care professional13. It was also shown in the present study that the respondent’s partners played a role in determining place of delivery; those women whose partners had formal jobs were more likely to deliver in a health facility as opposed to those whose partners’ job was casual or otherwise. The findings are similar to those of a study by Okang and Kaseje in Eritrea found that partners who had formal employment were more likely to deliver in a health facility than those with non-formal employment14.

Level of education is recognized as having an influence on the place of delivery. Women with non-formal education are more likely to deliver at home as opposed to a formally educated woman with a higher probability of delivering at a health facility15, as shown by studies carried out in Nepal, Columbia and Kenya16. Additionally a study by Feyissa and Genemo in Ethiopia showed that the level of education has a significant influence on health facility delivery15. Contrary to above, the results of this study in Mwingi North Subcounty show that education has little or no influence on the place of delivery. From the data obtained from our respondents, most of the women, irrespective of their level of education, delivered either at home or at a government health facility except for women with adult education who exclusively delivered at their own homes. This finding was in contrast to the anticipated results that would have shown a distinction in place of delivery depending on a woman’s educational attainment.

Similarly according to Addai13, in his study farming women were less likely to seek medical care at the time of delivery than women in other occupations. This was also influenced by the occupation of partners. This may be because partners with formal employment may be able to provide insurance cover; limitation of financial resources and poor access to health services are cited as the two reasons why farming woman give birth at home17.

Regarding health facility-related factors, most of the respondents in this study lived more than 10km from a health centre and therefore delivered at home due to the long distance from their homes to the heath facility. The number of ANC clinic visits were proportionately reduced; as distance increased the number of ANC visits decreased. Our study findings concur with Bhattacharyya et al.11 whose findings in a study in India showed that women who gave birth at home would rather have delivered at a health facility but the long distance accompanied by transport challenges proved to be a hindrance. Moreover, a study in Nepal by Devkota et al.18 drew a similar conclusion, where they found that approximately 18% of women who had intended to deliver at a health facility ended up delivering at home. These findings are in agreement with Kenya’s KDHS that showed that most of the health facilities are over 5km radius from the consumers of services19.

Conclusions

Health facilities are the preferred sites for delivery regardless of the level of education, marital status and occupation of the respondents. Multiparous women are less likely to give birth at a health facility in preference of home deliveries. Long distance from the health facility is a hindrance to accessing health services and in turn maternal health care from qualified medical practitioners in Mwingi North Subcounty, Kenya.

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Mutiiria MM, Mbugua GG and Marwanga D. Factors associated with health facility delivery in Kitui County: a cross sectional study [version 3; peer review: 1 approved, 1 approved with reservations, 2 not approved]. F1000Research 2024, 9:522 (https://doi.org/10.12688/f1000research.23419.3)
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Reviewer Report 13 Sep 2024
Hawraa Hussein Ghafel, University of Baghdad, Baghdad, Baghdad Governorate, Iraq 
Not Approved
VIEWS 3
Dear Editor
i hope you are well  
1.The research was conducted before  6 years ago. I find that  has been a long period of time. Circumstances have changed. The study is not updated
2.The results did not ... Continue reading
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Ghafel HH. Reviewer Report For: Factors associated with health facility delivery in Kitui County: a cross sectional study [version 3; peer review: 1 approved, 1 approved with reservations, 2 not approved]. F1000Research 2024, 9:522 (https://doi.org/10.5256/f1000research.158401.r279344)
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Reviewer Report 06 Jun 2024
Ferry Efendi, Universitas Airlangga, Surabaya, Indonesia 
Approved
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I have no ... Continue reading
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Efendi F. Reviewer Report For: Factors associated with health facility delivery in Kitui County: a cross sectional study [version 3; peer review: 1 approved, 1 approved with reservations, 2 not approved]. F1000Research 2024, 9:522 (https://doi.org/10.5256/f1000research.158401.r238897)
NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article.
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Reviewer Report 29 Feb 2024
Danish Ahmad, Indian Institute of Public Health Gandhinagar, Gandhinagar, India;  Australian National University, Canberra, Australia 
Approved with Reservations
VIEWS 6
The revised paper incorporates key reviewer comments. The authors are encouraged to address a few remaining changes.
1) In the methods section, please explicitly state the outcome and exposure variables as opposed to saying the paper has outcome and ... Continue reading
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Ahmad D. Reviewer Report For: Factors associated with health facility delivery in Kitui County: a cross sectional study [version 3; peer review: 1 approved, 1 approved with reservations, 2 not approved]. F1000Research 2024, 9:522 (https://doi.org/10.5256/f1000research.158401.r238896)
NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article.
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Reviewer Report 25 Jan 2023
Vernon Mochache, UNDP/UNFPA/UNICEF/WHO/World Bank Special Programme of Research, Development of Sexual and Research Training in Human Reproduction (HRP Research), Department of Sexual and Reproductive Health and Research, World Health Organization, Geneva, Switzerland 
Not Approved
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This is an interesting piece of work that would have ben valuable in determining policy at sub-national level in Kitui County. However, I have several concerns as illustrated below:

Background: The authors do a poor job of ... Continue reading
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Mochache V. Reviewer Report For: Factors associated with health facility delivery in Kitui County: a cross sectional study [version 3; peer review: 1 approved, 1 approved with reservations, 2 not approved]. F1000Research 2024, 9:522 (https://doi.org/10.5256/f1000research.129172.r159973)
NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article.
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Reviewer Report 26 Aug 2022
Danish Ahmad, Indian Institute of Public Health Gandhinagar, Gandhinagar, India;  Australian National University, Canberra, Australia 
Approved with Reservations
VIEWS 23
Thank you for revising the paper. I found your responses helpful but most of them seem to refute my suggestions. The reviewer comments are made to improve the readability of the paper and incorporating them enhances the likelihood that the ... Continue reading
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HOW TO CITE THIS REPORT
Ahmad D. Reviewer Report For: Factors associated with health facility delivery in Kitui County: a cross sectional study [version 3; peer review: 1 approved, 1 approved with reservations, 2 not approved]. F1000Research 2024, 9:522 (https://doi.org/10.5256/f1000research.129172.r147733)
NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article.
  • Author Response 02 Sep 2022
    Mathew Mutiiria, School of Health Sciences, Meru University of Science & Technology, Meru, Kenya, Meru, Kenya
    02 Sep 2022
    Author Response
    Thank Ahmed for your reviews

    1. Regarding the wards, I revised table 2 to include data from the wards. From the table 2, women who were attended in Mumoni ... Continue reading
COMMENTS ON THIS REPORT
  • Author Response 02 Sep 2022
    Mathew Mutiiria, School of Health Sciences, Meru University of Science & Technology, Meru, Kenya, Meru, Kenya
    02 Sep 2022
    Author Response
    Thank Ahmed for your reviews

    1. Regarding the wards, I revised table 2 to include data from the wards. From the table 2, women who were attended in Mumoni ... Continue reading
Version 1
VERSION 1
PUBLISHED 04 Jun 2020
Views
17
Cite
Reviewer Report 19 Oct 2021
Danish Ahmad, Indian Institute of Public Health Gandhinagar, Gandhinagar, India;  Australian National University, Canberra, Australia 
Approved with Reservations
VIEWS 17
The authors use cross sectional survey data collected from 245 women in a region of Kenya, Kitui county, to assess determinants of institutional delivery. The paper is set against the high rates of maternal mortality and countries having missed UN-MDG ... Continue reading
CITE
CITE
HOW TO CITE THIS REPORT
Ahmad D. Reviewer Report For: Factors associated with health facility delivery in Kitui County: a cross sectional study [version 3; peer review: 1 approved, 1 approved with reservations, 2 not approved]. F1000Research 2024, 9:522 (https://doi.org/10.5256/f1000research.25848.r96056)
NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article.
  • Author Response 16 Aug 2022
    Mathew Mutiiria, School of Health Sciences, Meru University of Science & Technology, Meru, Kenya, Meru, Kenya
    16 Aug 2022
    Author Response
    Thank you reviewer for spending valuable time looking at this article
    Find the following responses to the comments 

    I) The generalisability of the paper is limited due to a ... Continue reading
COMMENTS ON THIS REPORT
  • Author Response 16 Aug 2022
    Mathew Mutiiria, School of Health Sciences, Meru University of Science & Technology, Meru, Kenya, Meru, Kenya
    16 Aug 2022
    Author Response
    Thank you reviewer for spending valuable time looking at this article
    Find the following responses to the comments 

    I) The generalisability of the paper is limited due to a ... Continue reading
Views
23
Cite
Reviewer Report 01 Sep 2021
Ferry Efendi, Universitas Airlangga, Surabaya, Indonesia 
Approved
VIEWS 23
Interesting study regarding health facility delivery and the associated factors in Kitui County. My feedback as follows:

1. On the methods section please elaborate the inclusion criteria of this study.

2. Please explain your ... Continue reading
CITE
CITE
HOW TO CITE THIS REPORT
Efendi F. Reviewer Report For: Factors associated with health facility delivery in Kitui County: a cross sectional study [version 3; peer review: 1 approved, 1 approved with reservations, 2 not approved]. F1000Research 2024, 9:522 (https://doi.org/10.5256/f1000research.25848.r92076)
NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article.
  • Author Response 20 Sep 2021
    Mathew Mutiiria, School of Health Sciences, Meru University of Science & Technology, Meru, Kenya, Meru, Kenya
    20 Sep 2021
    Author Response
    Dear Reviewer,

    Thank you for spending your valuable time looking at this article. 
    Your comments are well noted and I will consider them to appear in version two of ... Continue reading
COMMENTS ON THIS REPORT
  • Author Response 20 Sep 2021
    Mathew Mutiiria, School of Health Sciences, Meru University of Science & Technology, Meru, Kenya, Meru, Kenya
    20 Sep 2021
    Author Response
    Dear Reviewer,

    Thank you for spending your valuable time looking at this article. 
    Your comments are well noted and I will consider them to appear in version two of ... Continue reading

Comments on this article Comments (0)

Version 3
VERSION 3 PUBLISHED 04 Jun 2020
Comment
Alongside their report, reviewers assign a status to the article:
Approved - the paper is scientifically sound in its current form and only minor, if any, improvements are suggested
Approved with reservations - A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.
Not approved - fundamental flaws in the paper seriously undermine the findings and conclusions
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