Factors associated with health facility delivery among reproductive age women in Nepal: An analysis of Nepal Multiple Indicator Cluster Survey 2019

Abstract

Background

Delivery in health facility is an essentials factor in improving maternal health. Reducing maternal mortality is the one of the targets of Sustainable Development Goal 3. Health facility delivery is still major concern in Nepal. This study aims to determine the factors associated with delivery in health facility among women aged 15-49 years in Nepal.

Methods  

This study used data from Nepal Multiple Indicator Cluster Survey 2019, a nationally representative cross-sectional survey. This survey was a two-stage, stratified cluster sampling. A total of 1,950 married women age 15-49 years who had at least one live birth in the last two years preceding the survey were included in the analysis. Bivariate and multivariate logistic regression analysis were performed in this study.

Results

Seventy-eight percent of women delivered in health facility. Women from urban area (AOR= 1.64, p<0.01), women residing in Sudurpaschim province (AOR=5.68, p<0.001), women who used internet (AOR=1.53, p<0.05), women with first parity (AOR=2.79, p<0.001), and women from richest household status (AOR= 6.10, p<0.005) and women who attained at least four ANC visits (AOR=12.77, p<0.001) were associated with higher odds of delivering in a health facility.

Conclusion

Consideration should be given to female education, poverty reduction and promotion of maternal healthcare services with particular attention to uneducated women or with low education levels, who reside in rural areas, women from poor household status and disparity in maternal health services across the provinces.

Background

Health facility delivery is one of the essential strategies to improve maternal health and reduce the risk of maternal and child morbidity and mortality [1–4]. The increment in health facility delivery is essential for reducing maternal death from pregnancy complication [5]. Delivery in a health facility also ensures safe birth and increases the survival of mothers as well as newborn children [6–8].  One of the Sustainable Development Goal (SDG) 3 targets  is  to reduce the global maternal mortality ratio to less than 70 per 100,000 live birth by 2030 [9].  Nepal has also committed to meeting this target by 2030 [10]. In order to achieve the targets of health facility delivery, the Nepal Health Sector Strategy 2015-2020 has set a target of achieving 70% health facility delivery by 2020 [11].     

Nepal is characterized by high maternal mortality ratio in South Asian Association of Regional Cooperation (SAARC) region except Afghanistan [12]. Reducing maternal mortality and morbidity is the national priority. The Government of Nepal has been implementing a safe motherhood program for improving maternal and newborn health focusing on health facility delivery [13]. Safe motherhood program in Nepal encourages health facility delivery through various incentives such as free delivery care and transportation incentive to mother after delivery in a health facility [3,14]. 

Health facility delivery is the delivery in health institutions, whether in government hospitals, public hospitals or private hospitals/clinics. Health facility delivery enables women to receive proper medical care during childbirth and reduces risk of maternal death. Nepal has made remarkable progress in delivery coverage in health facility as the percentage delivered in a health facility increased from 8% in 1996 to 57% in 2016 [15]. Delivery in a health facility is 95% in Maldives [16], 79% in India [17], 66% in Pakistan [18], 49% in Bangladesh [19], and 48% in Afghanistan [20]. Despite of national efforts to promote delivery in health facility, many women continue to deliver outside the health facilities in Nepal.  

Health facility delivery is determined by various factors. Previous studies have explored factors associated with health facility delivery [4,6,21–25].   Studies form Ghana [7], Indonesia  [26] and India [27] showed that household wealth, place of residence, attending Antenatal Care (ANC), parity, educational level, economic status, maternal age, age at marriage, women autonomy and mass media were significant factors that affect health facility delivery.  

The previous studies in Nepal have focused on factors associated with delivery in a health facility. These studies revealed that women's education, ANC visit [28–30], household wealth index [28,30], place of residence, women's autonomy, exposure to media [29], the distance to health facility [30] and birth preparedness [28] were a strong predictor for health facility delivery in Nepal. In addition to-date, limited studies [31] have conducted factors affecting health facility delivery using nationally representative data from the Nepal Multiple Indicator Cluster Survey 2019. The Nepal Multiple Indicator Cluster Survey is a nationally representative survey that aims is to provide high-quality data for monitoring the situation of women and children by collecting information on reproductive health, child health, education, social protection, environment, and access to mass media as well as demographic, socioeconomic and spatial characteristics of individuals and households [32]. Understanding the factors that influence health facility delivery is essential for any intervention to improve maternal health through delivery in a health facility. This study aims to determine the factors associated with delivery in a health facility among women aged 15-49 years in Nepal. The results of this study can contribute to designing the policies for improving maternal health through promoting health facility delivery in Nepal. 

Methods

Data sources

The data for this study were extracted from individual woman record of the Nepal Multiple Indicator Cluster Survey (MICS) 2019 datasets. This dataset is publicly available for researchers. Permission to access and use this dataset is obtained from UNICEF/MICS website (http://mics.unicef.org/surveys). The Nepal Multiple Indicator Cluster Survey is a nationally representative cross-sectional survey carried out in 2019 by Central Bureau of Statistics with the technical and financial support from the United Nations Children's Fund (UNICEF). This survey is a part of the Global MICS program. The objective of MICS was to monitor health status of women and children by various indicators. The survey collected information on socio-economic and demographic characteristics of households and household members, reproductive and maternal health, child mortality, child health, nutrition, literacy and education, child protection, attitudes towards domestic violence, knowledge of HIV/AIDS, access to media, and use of information and communication technology. 

Sample design

The Nepal MICS employed a two-stage, stratified cluster sampling approach. In the first stage, sampling strata were identified, and then census enumeration areas (EAs) were selected from each sampling strata. In the second stage, a sample of households was selected from each selected area using a listing of households. A detailed description of the sample design is available in the Nepal MICS report [32]. 

Sample size and study population 

In Nepal MICS, 12800 households were selected for the sample, of which 12655 households were interviewed. Likewise, 15019 women aged 15-49 years were identified eligible for interviews. However, 14805 women aged 15-49 years were successfully interviewed, yielding a 98.6 percent response rate. For this study, 1950 married women aged 15-49 years who had at least one live birth in the last two years preceding the survey were included in the study population.

Study variables

The study's dependent variable is the place of delivery for the most recent birth in the last two years before the survey. This variable is categorized into binary outcomes. Women who delivered in a public and private health sectors are coded 1 (or 'health facility'), and those reported to have delivered elsewhere other than public and private sectors are coded 0 (or 'home/elsewhere'). 

The independent variables for this study were selected based on the evidence from previous studies.  As presented in Table 1, the independent (or explanatory) variables included current age of women (15-19, 20-29, and 30-49 years), age of mother at most recent live birth (<20, 20-34, and 35-49 years), place of residence (rural/urban), province, women's education (no education, basic (grade1-8), secondary (grade 9-12), and higher), household wealth index (poorest, poor, middle, rich, and richest), parity, ANC visits (no, 1-3 visits, and 4+ visits), media exposure, use of internet, use of a mobile phone, and migration status (urban migrants, rural migrants, urban non-migrants and rural non-migrants). In this study, rural migrants are those who move from rural to another rural area or urban area. Urban migrants refer to those who move from an urban area to another urban or rural area. 

Table 1. Definition and categorization of study variables

 Data analysis

Data were analyzed using STATA version 15.1. Univariate analysis is carried out to analyze selected socio-demographic characteristics of women aged 15-49 years. Chi-square tests were used to determine the differentials and significant association between dependent and independent variables. Bivariate logistic regression was also carried out to examine the crude association between dependent and independent variables. Variables significant at the 0.05 level in bivariate logistic regression were included in the multivariate logistic regression analysis. Multi-collinearity assessment is performed prior to the multivariate analysis. The results of multivariate analysis are shown in odds ratios (OR). The critical level was set at a 95% confidence interval (CI). Sample weights were applied in all analyses. The complex survey design of MICS (primary sampling units and strata) was taken in logistic regression analysis. 

Results

Background characteristics of the respondents

Table 2 shows the background characteristics of women aged 15-49 years. Majority of the women (68%) are aged 20-29 years. About two third of women resided in urban area and one fifth of women in Province 2. About 21% of women had no education, 31% received basic education, and 40% received secondary education. Sixty-two percent of women reported having access to media and 44 % of women use internet.  Eighty-four percent women have mobile phones. Forty-four percent women belonged to first parity. 

Similarly, 78% of women had their recent birth at age 20-34 years. Ninety-five percent women have no health insurance. Considering migration status, 71% of women are rural migrants. About 64% of women are below the middle household wealth index quintile. Seventy-eight percent of women attended at least four ANC visits for the most recent birth within the survey's last two years.

 Table 2. Background characteristics of the respondents, Nepal MICS 2019

Association between background characteristics and place of delivery 

Table 3 shows that among 1950 women of reproductive age, 78% delivered at a health facility. Delivery in a health facility was higher among women aged 15-19 years (80%) and women in urban areas (84%).  Regarding provinces, the percentage of women delivering in a health facility was more than 78% in Gandaki, Bagmati, Sudurpaschim, Province 1 and Lumbini province. Similarly, the proportion of health facility delivery was higher among women with secondary and higher education, who were exposed to media, who used information and communication technology (internet and mobile phone), who had lower parity, with age of women at most recent birth was less than 20 years, who had health insurance, who were urban migrants, in highest wealth index quintile, and who attended ANC at least four visits. The percentage of delivery in a health facility increased with the level of education of women and with the level of household wealth index quintiles, frequency of mass media use, and the increase in ANC visits.  

Table 3.     Percent distribution of married women aged 15-49 years with a live birth in the last two years by place of delivery of most recent live birth, Nepal MICS 2019

The results of bivariate analysis showed that place of residence, province, women's education, exposure to media, use of the internet, having own mobile, parity, health insurance, migration status, household wealth quintile, and ANC visits were significantly associated with place of delivery at 95% confidence level (p<0.001). Age of women's most recent birth less than 20 was strongly associated with place of delivery at 95 % confidence level (p<0.05). Age of women was not found to have a significant association with place of delivery.  

Factors associated with health facility delivery 

The results of bivariate logistic regression analysis are presented in Table 4. Place of residence, province, women's education, access to media, internet use, having own mobile, parity, age of women at most recent live birth, health insurance, migration status, wealth index and ANC visits were significantly associated with health facility delivery. After adjusting the effects of other variables, place of residence, province, internet use, parity, household wealth index, and ANC visits remain significantly associated with health facility delivery. The adjusted odds ratio indicated that women living in urban areas were 1.64 times [AOR: 1.64, 95% CI: 1.17-2.30] more likely to deliver at health facility than women living in rural areas. The odds of delivering in a health facility were 5.86 [AOR:5.86, 95% CI: 3.15-10.90] times higher among women from Sudurpaschim, 3.06 times [AOR: 3.06, 95% 1.70-5.50] higher among women form Gandaki, 2.98 times [AOR: 2.98, 95% 1.55-5.74] higher among women form Karnali, 2.64 times [AOR: 2.64, 95% CI: 1.55-4.50] higher among women from Bagmati, 2.44 times [AOR: 2.44, 95% CI: 1.41-4.20] higher among women from Province 1 and 2.09 times [AOR: 2.09, 95% CI: 1.30-3.36] higher among women from Lumbini Province compared with women from Province 2. Women who used the internet were 1.53 times [AOR:1.53, 95% CI:1.09-2.14] more likely to deliver at health facility compared with women who did not use the internet. Parity was also significantly associated with delivering at health facility in adjusted odds ratio. The odds of delivering at health facility was 2.79 times [AOR:2.79, 95% CI:1.63-4.76] higher for women of one parity than women of four or more parities. The odds of delivering in a health facility increases as the level of household wealth index quintile increases. Women who attended at least four ANC visits had 12.77 times [AOR:12.77, 95% CI:6.69-2439] higher odds of delivering in a health facility than women who had no ANC visits.

Table 4. Logistic regression analysis of health facility delivery for the most recent live birth in the last 2 years preceding the survey, Nepal MICS 2019

*** p<0.001, ** p<0.01, * p<0.05

Note: COR = Crude odds ratio (unadjusted), AOR = Adjusted odds ratio

Discussion

The Government of Nepal has implemented various strategies to improve maternal and newborn health. This study explored the factors associated with delivery in health facility among women aged 15–49 years in Nepal. The results of this study showed that 78% of women delivered in a health facility. This result was, however, higher than that of Bangladesh [33]. Previous studies indicate that 59% of women are delivered in a health facility in Nepal [28]. This finding suggests that the increasing proportion of women who delivered in a health facility could be attributed to the various efforts and interventions that have been implemented by Government of Nepal to improve delivery in a health facility. These efforts include the expanding the birthing center, cash incentive, free delivery services and incentives for 4 ANC visits [34]. In addition, Free Delivery Care (FDC) policies have a more significant impact on improving access to and use of health facility for delivery [35]. This study found that residence, province, internet use, parity, wealth index, and ANC visits significantly influenced delivery in a health facility.

The study found that women's delivery in a health facility is influenced by place of residence. Women in an urban setting are more likely to deliver in a health facility. This finding is in line with previous studies from Nepal [36], India [27, 37], Indonesia [26], Ethiopia [22], Kenya [38] and Ghana [7, 39]. This finding could be attributed to easier access to maternal health services in urban areas than rural areas. There are great differences in access to maternal health services between urban and rural areas. Previous study in Nepal [40] and South Asia [41] suggested that women belonging to poor families, fewer health facilities, lack of reliable transportation to the health facility in rural areas may be contributing to less utilization of health facility delivery. However, another study in Nepal did not find significant association between delivery in a health facility and place of residence after adjusting the covariates [28].

This study revealed that provincial variation is an important predictor of delivery in a health facility. Following previous studies in Nepal [28, 30, 36], this study also showed that province of residence was significantly associated with the health facility delivery. This study indicated a significant difference between provinces in the use of health facility for delivery. The likelihood of health facility delivery was greater in Sudurpaschim and Gandaki Province. The unequal utilization of health facilities for delivery across provinces may be associated with disparities in the availability and utilization of maternal health services across the provinces [42]. However, there are limited studies that show the relationship between province and health facility delivery.

This study found that the use of the internet was positively associated with health facility delivery. Internet is the primary source of health-related information regarding pregnancy, healthy delivery and the importance of maternal healthcare utilization [43]. The use of the internet might help to increase awareness about maternal issues in the family, and they are motivated to use health facilities for delivery [44].

The results of this study releveled that women who had only first birth (first parity) were more likely to deliver in a health facility. This finding was consistent with previous studies in Nepal [45, 46], Ethiopia [47, 48], Ghana [7, 39, 49], and Senegal [50]. The possible explanation could be that women with higher parity may have self-confidence to deliver at home and not prefer to deliver in a health facility. However, first parity women may be afraid of complications in pregnancy and childbirth. Therefore, first parity women were more likely to deliver in a health facility.

Similar to the previous studies in Senegal [50], Kenya [51], Malawi [52] and India [53], this study identified that women in high household wealth were more likely to give birth in health facility compared with those in poor household wealth. Previous studies in Nepal [28, 30, 36, 46, 54] and low- and middle-income countries [55] found that household wealth index was positively associated with delivery in a health facility. Women who belong to higher household status have been educated and awareness of the importance of health facility delivery and have the financial capacity to pay travel and medical care expenses if necessary [56, 57]. The strong association of household wealth quintile with health facility delivery suggests that poor economic status is a barrier to health facility delivery. To reduce this barrier, the Government of Nepal has promoted safe motherhood through incentives such as free delivery care and transportation incentives scheme to women for delivering in a health facility.

This study found that the number of ANC visits was significantly associated with delivery in a health facility. Women who attended at least one ANC visits were more likely to deliver in a health facility. This results is consistent with previous studies conducted in Ethiopia [22, 58], Ghana [22], Nigeria [59] and Mozambique [60]. Previous studies in Nepal [3, 40, 46, 61, 62] demonstrated that ANC visits as a strong predictor of delivery in a health facility. Women who attended more ANC visits were more aware and had more information about danger signs during pregnancy. ANC visits allow mothers to contact health personal frequently and develop positive attitudes towards delivery in a health facility.

In contract to the finding of previous studies [29, 30, 60], women's education did not have a significant association with delivery in a health facility after adjusting other variables. The possible explanation for this result is that women's education level could affect health facility delivery through parity and ANC visits.

The main strength of this study is that it used nationally representative population-based data, which provides up-to-date figure on prevalence of health facility delivery and allows for generalization of the finding at the national level. This study did not include some potential factors that may affect the delivery in a health facility such as caste/ethnicity, religion, employment status of women, and distance to health facility. The purposively selected independent variables are included in the study. The findings of the study can be generalizing to the county.

Conclusion

The finding of the study revealed that the prevalence of delivery in a health facility is low among the women who reside in rural area, who are less educated, who are not exposed to media and use information and communication technology, who have no health insurance, who are rural non-migrants, who belong to poor household status and who do not attend ANC visits. To improve delivery in a health facility, emphasis must be given to 4 + ANC visits among women who reside in rural area and belong to poor households. The study also indicates that provinces are significantly associated with delivery in a health facility, but inequalities in delivery in a health facility among provinces persist. It is recommended that maternal health services be expanded and promoted to women from poor household status, especially who are residing in rural areas–considering the findings of this research. In addition, efforts to reduce provincial inequalities in maternal healthcare services are needed to improve delivery in health facility. Provincial inequality in utilization of health facilities for delivery should be focused on further research.

Abbreviations

ANC: Antenatal care

AOR: Adjusted odds ratio

CI: Confidence interval

DHS: Demographic and Health Survey

EA: Enumeration 

MICS: Multiple Indicator Cluster Survey

NDHS: Nepal Demographic and Health Survey

OR: Odds ratio

SBA: Skilled birth attendant

SDG: Sustainable development goal

SLC: School living certificate 

UNICEF: United Nations Children's Fund 

Declarations

Ethics approval and consent to participate

The Nepal Multiple Cluster Survey data are open access to researchers and available upon request. We have received permission from UNICEF through online registration to provide a brief description of research project. The survey protocol was approved by Central Bureau of Statistics (CBS) as per the Statistical Acts (1958).

Consent for publication

This study does not include data from any specific individual, so consent to publish is "Not Applicable".

Availability of data

The data used in this study are freely accessible at MICS website http://mics.unicef.org/surveys. We agree the attached terms and conditions for the data sharing policy.

Competing interests

The authors declare that they have no competing interests.

Founding

No funding.

Authors' contributions

NRT conducted data analysis, review literature, interpretation and drafted the paper, SPU involved in review literature and interpretation. All authors read the final manuscript and approved it.

Acknowledgments

We would like to express our sincere thanks to United Nations Children's Fund and Central Bureau of Statistics for providing access to Nepal MICS the dataset. We would like to extend our appreciation to reviewers for intensive review and valuable comments that substantially improve the paper.

Authors' information

Naba Raj Thapa holds a Masters of Philosophy (M.Phil.) in Population Studies from Tribhuvan University, Nepal. Currently he is an Associate Professor at Department of Population Studies, Ratna Rajyalaxmi Campus, Tribhuvan University, Nepal. Shanti Prasad Upreti holds a Master of Arts in Population Studies from Tribhuvan University, Nepal. He is currently affiliated with Population Department of Population Studies, Ratna Rajyalaxmi Campus.

References

1. Karkee R, Binns CW, Lee AH. Determinants of facility delivery after implementation of safer mother programme in Nepal : A prospective cohort study. BMC Pregnancy and Childbirth. 2013;13(193):1–7.
2. Shahabuddin ASM, Brouwere V De, Adhikari R, Delamou A, Bardaj A, Delvaux T. Determinants of institutional delivery among young married women in Nepal : Evidence from the Nepal Demographic and Health Survey, 2011. BMJ Open. 2017;7:1–9.
3. Shah R, Rehfuess EA, Maskey MK, Fischer R, Bhandari PB, Delius M. Factors affecting institutional delivery in rural Chitwan district of Nepal: A community-based cross-sectional study. BMC Pregnancy and Childbirth. 2015;15(27):1–14.
4. Assefa L, Alemayehu M, Debie A. Magnitude of institutional delivery service utilization and associated factors among women in pastoral community of Awash Fentale district Afar Regional State, Ethiopia. BMC Research Notes. 2018;11(162):4–9.
5. Ministry of Health and Population [Nepal], New ERA, ICF. Nepal demographic and health survey 2011. Calverton, Maryland: Ministry of Health and Population, New ERA, and ICF; 2012.
6. Kesterton AJ, Cleland J, Sloggett A, Ronsmans C. Institutional delivery in rural India : the relative importance of accessibility and economic status. BMC Pregnancy and Childbirth. 2010;10(30):1–9.
7. Kumbeni MT, Apanga PA. Institutional delivery and associated factors among women in Ghana: findings from a 2017–2018 multiple indicator cluster survey. International Health. 2021;0:1–7.
8. Chalise B, Chalise M, Bista B, Pandey AR, Thapa S. Correlates of continuum of maternal health services among Nepalese women: Evidence from Nepal Multiple Indicator Cluster Survey. PLoS ONE. 2019;14(4):1–11.
9. United Nations. Transforming our world: The 2030 agenda for sustainable development [Internet]. 2015. Available from: https://sustainabledevelopment.un.org/content/documents/21252030 Agenda for Sustainable Development web.pdf
10. National Planning Commission. Nepal sustainable development goals: Status and roadmap 2016-2030. Kathmandu: Government of Nepal, National Planning Commission; 2017.
11. Ministry of Health and Population. Nepal health sector strategy. Kathmandu: Government of Nepal, Ministry of Health and Population; 2015.
12. World Health Organization, UNICEF, UNFPA, The World Bank. Trends in maternal mortality 2000 to 2017: estimates by WHO, UNICEF, UNFPA, World Bank Group and the United Nations Population Division. Geneva: World Health Organization; 2019.
13. Department of Health Services. Annual Report: Department of Health Services 2075/76 (2019/19). Kathmandu: Government of Nepal, Ministry of Health and Population, Department of Health Services; 2019.
14. Devkota B, Maskey J, Pandey AR, Karki D, Godwin P, Gartoulla P, et al. Determinants of home delivery in Nepal - A disaggregated analysis of marginalised and non-marginalised women from the 2016 Nepal Demographic and Health Survey. PLoS ONE. 2020;15(1):1–17.
15. Ministry of Health N, New ERA, ICF. Nepal demographic and health survey 2016. Kathmandu: Ministry of Health, Nepal.; 2017.
16. Ministry of Health, ICF. Maldives demographic health survey 2016-17. Rockville, Maryland, USA: Ministy of Health and ICF; 2018.
17. International Institute for Population Sciences, ICF. National family health survey (NFHS-4), 2015-16: India. Mumbai: International Institute for Poulation Sciences (IIPS); 2017.
18. National Institute of Population Studies, ICF. Pakistan demographic and health survey 2017-18 [Internet]. Islamabad, Kaistan, and Rockville, Maryland: National Institute of Population Studies(NIPS) [Pakistan] and ICF; 2019. Available from: https://www.dhsprogram.com/pubs/pdf/FR354/FR354.pdf
19. National Institute of Population Research and Training, ICF. Bangladesh demographic and health survey 2017-18. Dhaka, Bangladesh, and Rockville, Maryland, USA: National Institute of Population Research and Training (NIPORT), and ICF; 2020.
20. Central Statistics Organization, ICF. Afghanistan demographic and health survey 2015. Kabul: Central Statistics Organization, Ministy of Public Health; 2017.
21. Kebede A, Hassen K, Teklehaymanot AN. Factors associated with institutional delivery service utilization in Ethiopia. International Journal of Women’s Health. 2016;8:463–75.
22. Ketemaw A, Tareke M, Dellie E, Sitotaw G, Deressa Y, Tadesse G, et al. Factors associated with institutional delivery in Ethiopia: A cross sectional study. BMC Health Services Research. 2020;20(1):1–6.
23. Bishanga DR, Drake M, van Teijlingen E, Mwanamsangu AH, Makuwani AM, Zoungrana J, et al. Factors associated with institutional delivery: Findings from a cross-sectional study in Mara and Kagera regions in Tanzania. PLoS ONE. 2018;13(12):1–15.
24. Yaya S, Bishwajit G, Ekholuenetale M. Factors associated with the utilization of institutional delivery services in Bangladesh. PLoS ONE. 2017;12(2):1–14.
25. Yaya S, Bishwajit G, Gunawardena N. Socioeconomic factors associated with choice of delivery place among mothers : A population-based cross-sectional study in Guinea-Bissau. BMJ Global Health. 2019;4:1–7.
26. Efendi F, Rihlatun A, Hadisuyatmana S, Kuswanto H, Lindayani L, Berliana SM. Determinants of Facility-Based Childbirth in Indonesia. The Scientific World Journal. 2019;2019:1–7.
27. Barman B, Roy A, Zaveri A, Saha J, Chouhan P. Determining factors of institutional delivery in India: A study from National Family Health Survey-4 (2015–16). Clinical Epidemiology and Global Health. 2020;8(4):1335–40.
28. Aryal KK, Sharma SK, Khanal MN, Bista B, Sharma SL, Kafle S, et al. Maternal health care in Nepal: Trends and determinants [Internet]. Rockville, Maryland, USA: ICF; 2018. (DHS Further Analysis Reports No. 118). Available from: https://dhsprogram.com/pubs/pdf/FA118/FA118.pdf
29. Adhikari R, Wagle A. Inequality in Institutional Delivery of the Recent Birth among Married Women in Nepal: A Trend Analysis. Research Square. 2020;1–19.
30. Neupane B, Rijal S, GC S, Basnet TB. A Multilevel Analysis to Determine the Factors Associated with Institutional Delivery in Nepal: Further Analysis of Nepal Demographic and Health Survey 2016. Health Services Insights. 2021;14:1–10.
31. Pokhrel T, Adhikari R, Arya K, Gurung R, Dulal BP, Dahal HR. Socioeconomic Determinants of Inequalities in use of Sexual and Reproductive Health Services among Currently Married Women in Nepal.A further analysis of NMICS 2019 and NDHS 2016. Kathmandu; 2021.
32. Central Bureau of Statistics. Nepal multiple indicator cluster survey 2019: Survey finding report. Kathmandu: Central Bureau of Statistics and UNICEF Nepal; 2019.
33. Bangladesh Bureau of Statistics, UNICEF Bangladesh. Bangladesh multiple indicator cluster survey 2019, Survey findings report. Dhaka: Bangladesh Bureau of Statistics; 2019.
34. Ministry of Health and Population. Safe motherhood programe [Internet]. 2021. Available from: http://www.mohp.gov.np/eng/program/reproductive-maternal-health/safe-motherhood-programme
35. Bhatt H, Tiwari S, Ensor T, Ghimire DR, Gavidia T. Contribution of Nepal’s free delivery care policies in improving utilisation of maternal health services. International Journal of Health Policy and Management [Internet]. 2018;7(7):645–55. Available from: https://doi.org/10.15171/ijhpm.2018.01
36. Bhattarai P. Factors associated with use of maternal health services in Nepal: Analysis of the 2016 Nepal demographic and health survey. Journal of Nepal Health Research Council. 2019;17(3):301–7.
37. Paul PL, Pandey S. Factors influencing institutional delivery and the role of accredited social health activist (ASHA): a secondary analysis of India human development survey 2012. BMC Pregnancy and Childbirth. 2020;20(1):1–9.
38. Andegiorgish AK. Determinants of institutional delivery in Kenya . Evidence from population and Demographic health survey, 2014. Research Square. 2021;
39. Dankwah E, Zeng W, Feng C, Kirychuk S, Farag M. The social determinants of health facility delivery in Ghana. Reproductive Health. 2019;16(1):1–10.
40. Gautam S, Jeong HS. The role of women’s autonomy and experience of intimate partner violence as a predictor of maternal healthcare service utilization in Nepal. International Journal of Environmental Research and Public Health. 2019;16(5).
41. Shani P, De Kok B, Tamang PD. Inequity in the utilization of maternal-health care services in South Asia: Nepal, India and Sri Lanka. International Journal of Health Sciences and Research. 2017;7(1):271–81.
42. Ministry of Health and Population. Inequalities in maternal health service utilisation in Nepal: An analysis of routine and survey data 2018 [Internet]. Kathamandu; 2018. Available from: https://www.nhssp.org.np/Resources/HPP/Inequalities_in_maternal_hs_Nov2018.pdf
43. Laugesen J, Hassanein K, Yuan Y. The Impact of Internet Health Information on Patient Compliance: A Research Model and an Empirical Study. Journal of Medical Internet Research [Internet]. 2015;17(6):e143–e143. Available from: https://pubmed.ncbi.nlm.nih.gov/26068214
44. Javanmardi M, Noroozi M, Mostafavi F, Ashrafi-Rizi H. Internet usage among pregnant women for seeking health information: A review article. Iranian Journal of Nursing and Midwifery Research. 2018;23(2):79–86.
45. Kumar BR, Kumar DK. Determinants of utilization of institutional delivery services in East Nepal: A community-based cross- sectional study. Med Phoenix. 2018;3(1):6–15.
46. Freidoony L, Ranabhat CL, Kim CB, Kim CS, Ahn DW, Doh YA. Predisposing, enabling, and need factors associated with utilization of institutional delivery services: A community-based cross-sectional study in far-western Nepal. Women and Health [Internet]. 2018;58(1):51–71. Available from: http://dx.doi.org/10.1080/03630242.2016.1267689
47. Mitikie KA, Wassie GT, Beyene MB. Institutional delivery services utilization and associated factors among mothers who gave birth in the last year in Mandura district, Northwest Ethiopia. PLoS ONE. 2020;15(12):1–17.
48. Berelie Y, Yeshiwas D, Yismaw L, Alene M. Determinants of institutional delivery service utilization in Ethiopia: A population based cross sectional study. BMC Public Health. 2020;20(1):1–10.
49. Dickson KS, Adde KS, Amu H. What influences where they give birth? Determinants of place of delivery among women in rural Ghana. International Journal of Reproductive Medicine. 2016;2016:1–8.
50. Zegeye B, Ahinkorah BO, Idriss-Wheelr D, Oladimeji O, Olorunsaiye CZ, Yaya S. Predictors of institutional delivery service utilization among women of reproductive age in Senegal: a population-based study. Archives of Public Health. 2021;79(1):1–11.
51. Kitui J, Lewis S, Davey G. Factors Influencing Place of Delivery for Women in Kenya : An Analysis of the Kenya Demographic and Health Survey , 2008 / 2009. BMC Pregnancy and Childbirth. 2013;30(1):1–10.
52. Ntenda PAM. Women’s status within the household as a determinant of institutional delivery in Malawi. Midwifery. 2019;74:44–56.
53. Mondal D, Karmakar S, Banerjee A. Women’s autonomy and utilization of maternal healthcare in India: Evidence from a recent national survey. PLoS ONE. 2020;15(12):1–12.
54. Thapa NR, Adhikari S, Budhathoki PK. Influence of internal migration on the use of reproductive and maternal health services in Nepal: An analysis of the Nepal Demographic and Health Survey 2016. PLoS ONE. 2019;14(5):1–14.
55. Hasan M. M, Magalhaes RJS, Fatima Y, Ahmed S, Mamun AA. Levels, trends, and inequalities in using institutional delivery services in low- And middle-income countries: A stratified analysis by facility type. Global Health Science and Practice. 2021;9(1):78–88.
56. Atake E. Socio-economic inequality in maternal health care utilization in Sub-Saharan Africa: Evidence from Togo. The International Journal of Health Planning and Management [Internet]. 2021 Mar 1;36(2):288–301. Available from: https://doi.org/10.1002/hpm.3083
57. Tesfaye B, Mathewos T, Kebede M. Skilled delivery inequality in Ethiopia: To what extent are the poorest and uneducated mothers benefiting? International Journal for Equity in Health. 2017;16(1):1–8.
58. Delele TG, Biks GA, Abebe SM, Kebede ZT. Determinants of health facility delivery in Northwest Ethiopia: A community-based case-control study. International Journal of General Medicine. 2021;14:993–1001.
59. Dahiru T, Oche OM. Determinants of antenatal care, institutional delivery and postnatal care services utilization in Nigeria. Pan African Medical Journal. 2015;21:1–17.
60. Yaya S, Idriss-Wheeler D, Shibre G, Amouzou A, Bishwajit G. Prevalence of institutional delivery and its correlates amongst women of reproductive age in Mozambique: A cross-sectional analysis. Reproductive Health. 2020;17(1):1–11.
61. Shrestha SK, Banu B, Khanom K, Ali L, Thapa N, Stray-Pedersen B, et al. Changing trends on the place of delivery: Why do Nepali women give birth at home? Reproductive Health. 2012;9(1):1–8.
62. Tamang JP, McNeil R, Tongkumchum P. Factors Associated with Non-Institutional Delivery among Pregnant Women in Nepal. Asian Social Science. 2019;15(7):43.