Skip to main content
Download PDF
  • Research article
  • Open access
  • Published:

Determinants of early initiation of breastfeeding in Ethiopia: a population-based study using the 2016 demographic and health survey data

BMC Pregnancy and Childbirth volume 19, Article number: 69 (2019) Cite this article

Abstract

Background

Timely breastfeeding initiation is a simple but important measure that has protective effects on infants and mothers. This study aims to determine the predictors of early breastfeeding initiation among mothers residing in Ethiopia.

Methods

This study employed the 2016 Ethiopian Demographic and Health Survey data. A total of 5546 children born during the last 24 months at the time of survey were included for analysis from nine regional states and two city administration areas. Socio-demographic and socio-economic factors including individual, household and community-level factors were examined of their significance against the outcome variable of early initiation of breastfeeding using a mixed-effect logistic regression model.

Results

The proportion of infants who had timely initiation of breastfeeding was 74.3% (n = 3064). In the multivariate logistic regression analysis, mothers who delivered with assistance of one or more health professionals had 68% (AOR 1.68; 95% CI: 1.23, 2.29) higher odds of initiating timely breastfeeding. In addition, mothers delivering by a caesarean section had 86% reduced odds of early breastfeeding initiation (AOR 0.14; 95% CI: 0.09, 0.22) when compared to mothers who had vaginal delivery. In terms of socio-demographic factors, the odds of early breastfeeding initiation were more than two and half times higher particularly for mothers residing particularly in Oromiya (AOR 2.58; 95% CI: 1.84, 3.63) and Southern Nations Nationalities and Peoples (SNNP) (AOR 2.75; 95% CI: 1.86, 4.05). In addition, timely breastfeeding initiation was also significantly associated with wealth index with wealthier mothers having 43% higher odds compared to mothers of poorest households (AOR 1.43; 95% CI: 1.07, 1.92). Other factors such as age, gender and birth order of the infant also had significant associations with early breastfeeding initiation.

Conclusion

Early breastfeeding initiation in Ethiopia is inextricably associated with various socio-demographic, biomedical, and socio-economic factors. The study findings can potentially inform mothers and the wider community on the benefits of timely breastfeeding initiation and policymakers and community leaders to target health promotional interventions and resources where needed.

Peer Review reports

Introduction

Breastfeeding is an essential primary health care practice for optimal care of a newborn infant [1]. Early initiation of breastfeeding (EIBF) is referred to as feeding through mother’s breast milk to newborn infants within first hour of birth [2]. EIBF has profound implications for both infants and mothers in terms of nutritional, developmental and immunological outcomes [3]. Practice of EIBF enables provision of immunoglobulin and other essential bioactive molecule-rich colostrum for newborn infants that are critical for their immunity, growth and development [4]. There is sound evidence indicating that EIBF is strongly associated with reduced mortality among neonatal and newborn infants [5]. Furthermore, research indicates that EIBF promotes “Maternal-Infant Bonding” resulting in beneficiary outcomes for child’s development [6]. EIBF practice is also proven to have both short and long-term benefits to mothers as it reduces postpartum haemorrhage, lowers risk of obesity post-delivery, improve birth spacing period and reduces the risk of breast and ovarian cancer in the long run [1, 7, 8].

While the health benefits of EIBF are well-recognised, a significant percentage of newborns infants continue not to be breastfed within the first hour as per the World Health Organization (WHO) recommendation. Research indicates that the average prevalence of EIBF is 64% in 128 countries, with one-half of the countries having prevalence of less than 50% [9]. Ethiopia is one of the countries that have implemented several initiatives for improving access and availability of primary care services particularly after the launch of the Health Promotion Program in 2003. Evidence shows a predominant increase in the number of health workforce particularly in rural regions of Ethiopia to promote basic health awareness and intervention [10]. The Ethiopian government has recognized the importance of EIBF and other nutrition programs through National reforms and strategies on infant and young child feeding practices [11]. Recent Demographic Health Survey (DHS) report shows that 74.3% of newborn infants were breastfeed within first hour of birth and infant mortality was estimated to be 48 deaths per 1000 live births [12].

Despite improvements in the prevalence of EIBF from 52% in 2011 to 74.3% in 2016, this percentage still falls well short of the EIBF target of 92% set by the Ethiopian Ministry of Health’s Health Sector Development Program Four (HSDP-IV) [13]. This indicates the presence of existing barriers or new barriers that necessitates further investigations. In addition to this knowledge gap, although there are literatures reporting several drivers and barriers of EIBF across different communities in Ethiopia, most studies are small scale [14,15,16,17,18,19] or have not used the appropriate definition of timely initiation of breastfeeding as recommended by the WHO [20].

Therefore, there is a strong need of more comprehensive understanding of the current underlying factors of EIBF among mothers of infants under the age of 24 months on a nationally representative sample in Ethiopia. Therefore, this study aims to use the 2016 Ethiopian Demographic and Health Survey (EDHS) to determine individual, household and community level factors that predict EIBF in mothers of infants aged less than 24 months.

Methods

Data source, sampling and data collection

The data for this study was extracted from the 2016 EDHS. The 2016 EDHS is the fourth and most recent in the Demographic and Health Survey series in Ethiopia [12]. The survey was conducted in nine regional states and two city administrations of Ethiopia [12]. Further details on sampling strategy can be found in the DHS manual [12].

A total of 16,583 eligible women between 15 and 49 years were approached to be interviewed. A response rate of 95% was observed with 15,683 women completing the interviews. This included both women who were permanent household residents as well as visitors of the household. The interviews included several standard questionnaires recording information ranging from basic socio-demographic information to detailed bio-medical information. Our analysis only included children less than 24 months of age, living with an eligible respondent, in accordance with the denominator of the EIBF definition [2], which resulted in a total weighted sample of 5546.

Outcome variable

We used EIBF as the outcome variable using the recommended definition as children less than 24 months of age who were breastfed within first hour of birth [2]. This indicator was self-reported by mothers.

Co-variates

The co-variates included individual, household, and community level actors. Individual factors included socio-demographic characteristics such as mother’s highest education level (categorised as “no education”, “primary”, “secondary or above”) and employment status in the past 12 months (“not working” or “working”), partner’s highest educational level (“no education”, “primary”, “secondary or above”) and employment status (“not working”, “non-agriculture” and “agriculture”), marital status (“never married”, “currently married”, “formerly married”), mother’s age (“15–24 years”, “25–34 years”, “35–49 years”), child’s age (“0–5 months”, “6–11 months”, “12–17 months”, “18–23 months”), and mothers exposure to mass media (“no” or “yes”).

Bio-medical factors included the number of antenatal clinic visits (categorised as “0 visits”, “1–3 visits”, “4 or more visits”), place of delivery (“home” or “health facility”) and mode of delivery (“caesarean section” or “vaginal”), type of delivery assistance (“health professional”, “Traditional birth attendants”, “relatives/untrained workers”, “none”) and mother’s body mass index (BMI) measured by measured by weight (kg)/height (m2).

Household factors included household wealth index (categorised as “poorest”, “poorer”, “middle”, “richer” and “richest”), The household wealth index was calculated using scores based on household assets with analyses conducted by the National Population Commission and Inner City Fund (ICF) International based on a methodology developed from previous DHSs [21, 22] and using methods recommended by the World Bank Poverty Network and United Nations International Children’s Emergency Fund (UNICEF) [23].

Community level factors recorded were the place of residence (“rural” or “urban”) and geographical region. The geographical regions were grouped into nine regional states of Ethiopia; namely Afar, Amhara, Benishangul-Gumuz, Gambella, Harari, Oromia, Somali, Southern Nations Nationalities and Peoples’ Region (SNNP), and Tigray, and two city administrations named Addis Ababa and Dire Dawa [12].

Statistical analysis

Sampling weights were applied for all analyses to manage sampling error and for non-responses. Further details on sample weights can be found in the EDHS report [24].

Descriptive statistics were employed to show the distribution of background characteristics. Since, the survey data were nested in nature with variations among clusters (enumeration areas), we used mixed-effect logistic regression model to determine the true association between timely initiation of breastfeeding and different factors. We considered determinants as fixed effect and cluster variation as random effect. The parameters of the model were estimated through generalised estimating equation (GEE) approach by considering exchangeable correlation structure among clusters [25]. The full model was run with those variables showing P < 0.25 in the unadjusted analysis [26]. Meanwhile, the final model was reduced using the backward stepwise procedure and all the variables in the final model were variables for which P ≤ 0.05. Both unadjusted and adjusted odds ratios (ORs) were reported with 95% confidence intervals (95% CI). All analyses were performed using statistical software Stata (Version 13.0).

Ethics approval

This study is a secondary analysis of publicly available dataset where permission was obtained through registering with the DHS website and therefore no ethics approval was required.

Results

Baseline characteristics

The prevalence of EIBF in Ethiopia was observed to be 74.3% (n = 3064). As summarised in Table 1, a predominant percentage of the children lived in rural areas (87.9%), especially in the regions of Oromiya (44.7%) and SNNP (20%). 59% of mothers reported not working in the past 12 months at the time of survey, and 61% did not have any formal education. In addition to education status, around 72% of mothers reported having poor literacy skills and could not read or write a sentence.

Table 1 Individual, household and community level characteristics of children < 24 months of age, Ethiopia 2016
Full size table

In terms of mothers’ age, overall 51% of mothers were between 25 and 34 years of age at the time of having their first child. Most mothers (95%) reported as currently married at the time of the survey. Of the total births, only 38.5% took place at a health care facility with very low percentage of deliveries by caesarean section (2.6%). In terms of the number of antenatal visits, about 32% of mothers reported to have made at least 1–3 antenatal clinic visits and 33.5% had made more than 4 visits during pregnancy.

Predictors of EIBF

Of the total sample of 5546 children born in the last 24 months at the time of survey, 73.4% (n = 3064) of infants were breastfed within first hour of birth. Table 2 shows unadjusted and adjusted odds ratios (AOR) that were calculated to determine the strength of association between the co-variates and EIBF. As expected, mothers who delivered with assistance of one or more health professionals had 68% (AOR 1.68; 95% CI: 1.23,2.29) higher odds of initiating timely breastfeeding. In addition, type of delivery had significant association with mothers delivering by caesarean section having 86% reduced odds of early breastfeeding initiation (AOR 0.14; 95% CI: 0.09,0.22) compared to mothers who had vaginal delivery.

Table 2 Unadjusted and adjusted Odds Ratio for early initiation of breastfeeding in Ethiopia 2016
Full size table

Demographically, the odds of early breastfeeding initiation were more than two and half times higher particularly for mothers residing particularly in regions such as Oromiya (AOR 2.58; 95% CI: 1.84,3.63) and SNNP (AOR 2.75; 95% CI: 1.86,4.05) compared to mothers residing in Tigray. In addition, timely breastfeeding initiation was also significantly associated with wealth index where mothers from wealthier households had 43% higher odds compared to mothers from poorest households (AOR 1.43; 95% CI: 1.07,1.92). Female infants had 17% higher odds of EIBF (AOR 1.17; 95% CI: 1.01, 1.34) compared to male infants. Finally, EIBF was also associated with birth order with recently born children having higher odds of EIBF (AOR 1.44; 95% CI: 1.18, 1.77).

Discussion

This study showed that overall 7 out of 10 infants were being breastfed within the first hour of birth. Although, this prevalence has significantly improved in the five-year period from 52% in 2011 to 73.4% in 2016, it is still lower when compared to EIBF prevalence in other countries such as Malawi (95.64%), Mozambique (77.74%) and Rwanda (81.51%) [27]. However, the overall prevalence of EIBF in Ethiopia is much higher compared to Central African countries as well as West African countries [27]. This wide variation in the rates of EIBF within Ethiopia and between other African countries is likely due to geographic and cultural differences coupled with economic and health inequalities among different populations.

There was a statistically significant association between EIBF and the following covariates: (i) biomedical factors - type of delivery assistance, (ii) mode of delivery; socio-demographic factors - region, age, gender and birth order of child and (iii) socio-economic factor – wealth index. The predictors of EIBF of 2016 EDHS widely differs from that of the 2011 EDHS [20]. This may be due to several factors not limited to changes in health workforce and infrastructure, changes in nutrition and feeding policies, rural-urban migration, improved education and advancements in medicine and technology [28].

In our study, mothers who delivered with assistance of one or more health professionals had 68% higher odds of timely breastfeeding initiation compared to mothers with no assistance at the time of delivery. This is not surprising as primary health care professionals such as midwives or other trained health professionals would readily inform and assist mothers in the process of achieving timely initiation [29]. This finding is also consistent with findings from within and outside Ethiopia [30, 31].

Similar to existing research in Ethiopia and internationally [16, 17, 32, 33], a strong inverse association was observed between caesarean section and EIBF. Research suggest that mothers with caesarean section fail to initiate timely breastfeeding as they are often hindered by several barriers such as lengthy post-delivery hospital stays, prolonged mother-child separation, delayed skin-to-skin contact and maternal endocrinological diseases [7, 34]. Since delivery through caesarean section is becoming an increasingly common type of delivery, it is imperative to provide services that inform mothers about the importance of EIBF and its wide benefits to their newborn babies and themselves.

Distribution of EIBF rates is significantly different across the regional states in Ethiopia. Mothers from Oromiya, SNNP and Somali had significantly higher odds of EIBF whereas Affar had significantly lower odds of EIBF compared to mothers from Tigray. Other regions such as Harari, Dire Dawa, Gambella also had higher odds of EIBF but may be inconclusive given the low proportion of residents in those regions. This could be due to reasons of better access and availability of health resources in Oromiya, SNNP and Somali compared to Tigray and Afar.

In this study, female infants had higher odds of EIBF compared to male infants. This could potentially be due to the African cultural beliefs that male infants privileged enough to receive prelacteal feeds are accepted by the society as strong and healthy. The practice of prelacteal feeds in male infants is a common practice in African [35, 36] and Asian countries [37, 38].

This study also found a positive association between EIBF and child’s birth order. This is due to the fact that previous breastfeeding experience was positively associated with both intention as well as timely breastfeeding initiation [39]. This positive experience may be due to positive changes in beliefs regarding breastfeeding, where a mother found to benefit from timely breastfeeding initiation may decide to breastfeed a subsequent child in a timely manner. This finding is also consistent with findings from Amibara district of North-Eastern Ethiopia [17].

As expected, mothers from wealthier households had significantly higher odds of EIBF compared to mothers from poorest households. This could be due to several reasons such as better access and availability of health resources and better intellectuality through high quality education. Similar findings have been reported elsewhere [7, 40].

Policy and practice implications

EIBF rates in Ethiopia have significantly improved in the five-year period possibly as a result of improvement in health workforce, feeding policy, maternal and child health awareness programs. However, this study shows that there are still 3 in 10 infants who are not being breastfed in a timely manner and are not benefitting from the timely initiation, thereby prone to potential health risks. Therefore, a substantial increase in EIBF practice can be achieved by better informing mothers residing regional areas with less access to health services, mothers delivering through caesarean section with less birth term intervals. In addition, primary health care services must also be aimed at mothers from a poorer economic status with adequate resources and counselling about the beneficiary impacts of timely initiation of breastfeeding.

Strengths and limitations

One of the strengths of this study is that we used data from the 2016 EDHS which is a national survey. Therefore, the study findings have profound implications at person-level, community-level as well as policy-level. However, some local areas represented in the survey had small sample sizes, and thus the results should be interpreted with caution. Since this study is a secondary data analysis of a national survey, other key variables such as traditional beliefs, psycho-social factors, partner’s preference for breastfeeding, in-depth qualitative views of the mothers are not included. This study is based on cross-sectional data and hence it is difficult to demonstrate the cause and effect relationships of the co-variates on timely initiation of breastfeeding and the survey responses may be prone to a recall bias.

Conclusion

Timely initiation of breastfeeding in Ethiopia is inextricably associated with socio-demographic, bio-medical, and socio-economic factors. Health promotion programs for timely initiation of breastfeeding should be targeted towards mothers residing in the rural Ethiopian communities, those who are more likely to have a caesarean delivery. In addition, primary health care services must also be aimed to better inform mothers from a poorer household by providing adequate resources and counselling about the short and long-term benefits of EIBF to their newborn babies and themselves.

Abbreviations

AOR:

Adjusted odds ratio

BMI:

Body mass index

CI:

Confidence interval

DHS:

Demographic health survey

EDHS:

Ethiopian demographic and health survey

EIBF:

Early initiation of breastfeeding

GEE:

Generalised estimating equation

HSDP:

Health sector development program

ICF:

Inner city fund

SNNP:

Southern nations nationalities and peoples

UNICEF:

United nations international children’s fund

WHO:

World health organization

References

  1. Victora CG, Bahl R, Barros AJ, França GV, Horton S, Krasevec J, et al. Breastfeeding in the 21st century: epidemiology, mechanisms, and lifelong effect. Lancet. 2016;387(10017):475–90.

    Article  Google Scholar 

  2. World Health Organisation. Indicators for assessing infant and young child feeding practices: part 1: definitions: conclusions of a consensus meeting held 6-8 November 2007 in Washington DC. In: USA; 2008. http://apps.who.int/iris/bitstream/handle/10665/43895/9789241596664_eng.pdf;jsessionid=C8265C35AF29B66BC7F40E8879D8BB52?sequence=1 Accessed 24 July 2018.

    Google Scholar 

  3. Rollins NC, Bhandari N, Hajeebhoy N, Horton S, Lutter CK, Martines JC, et al. Why invest, and what it will take to improve breastfeeding practices? Lancet. 2016;387(10017):491–504.

    Article  Google Scholar 

  4. UNICEF. Infant and Young Child Feeding. Nutrition Section, Programmes, UNICEF New York. 2012. https://www.unicef.org/nutrition/files/Final_IYCF_programming_guide_June_2012.pdf. Accessed 28 July 2018.

  5. Group NS. Timing of initiation, patterns of breastfeeding, and infant survival: prospective analysis of pooled data from three randomised trials. The. Lancet Glob Health. 2016;4(4):e266–e75.

    Article  Google Scholar 

  6. Himani BK, Kumar P. Effect of initiation of breastfeeding within one hour of the delivery on “maternal-infant bonding”. Nurs Midwifery Res J. 2011;7(3):99–109.

    Google Scholar 

  7. Berde AS, Yalcin SS. Determinants of early initiation of breastfeeding in Nigeria: a population-based study using the 2013 demograhic and health survey data. BMC Pregnancy Childbirth. 2016;16(1):32–40.

    Article  Google Scholar 

  8. Luan N-N, Wu Q-J, Gong T-T, Vogtmann E, Wang Y-L, Lin B. Breastfeeding and ovarian cancer risk: a meta-analysis of epidemiologic studies. Am J Clin Nutr. 2013;98(4):1020–31.

    Article  CAS  Google Scholar 

  9. Takahashi K, Ganchimeg T, Ota E, Vogel JP, Souza JP, Laopaiboon M, et al. Prevalence of early initiation of breastfeeding and determinants of delayed initiation of breastfeeding: secondary analysis of the WHO global survey. Sci Rep. 2017;7:44868.

    Article  CAS  Google Scholar 

  10. United States Agency for International Development. All Eyes on Ethiopia’s National Health Extension Program 2015. https://2012-2017.usaid.gov/results-data/success-stories/all-eyes-ethiopia%E2%80%99s-national-health-extension-program-0 Accessed 29 July 2018.

  11. Federal Ministry of Health. National strategy for Infant and Young Child Feeding (IYCF). Family Health Department Ethiopia. 2004. https://extranet.who.int/nutrition/gina/sites/default/files/ETH%202004%20National%20Strategy%20for%20Infant%20and%20Young%20Child%20Feeding.pdf. Accessed 21 June 2018.

  12. Central Statistical Agency (CSA) [Ethiopia] and ICF. 2016 Ethiopia Demographic and Health Survey Key Findings. 2017. https://dhsprogram.com/pubs/pdf/SR241/SR241.pdf Accessed 18 June 2018.

  13. Ethiopian Ministry of Health. Health Sector Development Program Four (HSDP-IV) 2010. http://tucghe.org/HSDP%20IV.pdf. Accessed 16 June 2018.

  14. Hailemariam TW, Adeba E, Sufa A. Predictors of early breastfeeding initiation among mothers of children under 24 months of age in rural part of West Ethiopia. BMC Public Health. 2015;15(1):1076.

    Article  Google Scholar 

  15. Setegn T, Gerbaba M, Belachew T. Determinants of timely initiation of breastfeeding among mothers in Goba Woreda, south East Ethiopia: a cross sectional study. BMC Public Health. 2011;11(1):217.

    Article  Google Scholar 

  16. Tilahun G, Degu G, Azale T, Tigabu A. Prevalence and associated factors of timely initiation of breastfeeding among mothers at Debre Berhan town, Ethiopia: a cross-sectional study. Int Breastfeed J. 2016;11(1):27.

    Article  Google Scholar 

  17. Liben ML, Yesuf EM. Determinants of early initiation of breastfeeding in Amibara district, northeastern Ethiopia: a community based cross-sectional study. Int Breastfeed J. 2016;11(1):7.

    Article  Google Scholar 

  18. Bimerew A, Teshome M, Kassa GM. Prevalence of timely breastfeeding initiation and associated factors in Dembecha district, north West Ethiopia: a cross-sectional study. Int Breastfeed J. 2016;11(1):28.

    Article  Google Scholar 

  19. Beyene MG, Geda NR, Habtewold TD, Assen ZM. Early initiation of breastfeeding among mothers of children under the age of 24 months in southern Ethiopia. Int Breastfeed J. 2017;12(1):1.

    Article  Google Scholar 

  20. Lakew Y, Tabar L, Haile D. Socio-medical determinants of timely breastfeeding initiation in Ethiopia: evidence from the 2011 nation wide demographic and health survey. Int Breastfeed J. 2015;10(1):24.

    Article  Google Scholar 

  21. Central Statistical Authority/Ethiopia and ORC Macro. Ethiopia Demographic and Health Survey 2000. Addis Ababa, Ethiopia; 2001. https://www.dhsprogram.com/pubs/pdf/FR118/FR118.pdf. Accessed 11 July 2018.

  22. Central Statistical Authority/Ethiopia and ORC Macro. Ethiopia Demographic and Health Survey 2005. Addis Ababa, Ethiopia; 2006. https://www.dhsprogram.com/pubs/pdf/fr179/fr179%5B23june2011%5D.pdf. Accessed 21 June 2018.

  23. Filmer D, Pritchett L. Estimating wealth effects without expenditure data or tears: an application to educational enrollments in states of India. Demography. 2001;38(1):115–32.

    CAS  PubMed  Google Scholar 

  24. Central Statistical Agency/Ethiopia and ICF International. Ethiopia Demographic and Health Survey 2011. Addis Ababa, Ethiopia 2012. https://dhsprogram.com/pubs/pdf/fr255/fr255.pdf. Accessed 20 June 2018.

  25. Hanley JA, Negassa A, Forrester JE. Statistical analysis of correlated data using generalized estimating equations: an orientation. Am J Epidemiol. 2003;157(4):364–75.

    Article  Google Scholar 

  26. Agresti A. Introduction to general linear models. In: Agresti A. Categorical data analysis. Wiley; 2003. p. 115–164.

  27. Issaka AI, Agho KE, Renzaho AM. Prevalence of key breastfeeding indicators in 29 sub-Saharan African countries: a meta-analysis of demographic and health surveys (2010–2015). BMJ Open. 2017;7(10):e014145.

    Article  Google Scholar 

  28. World Health Organisation Regional Office for Africa. Issues and challenges - Progress on the Health-Related MDGs. 2018. http://www.aho.afro.who.int/en/ahm/issue/11/reports/progress-health-related-mdgs-african-region. Accessed 29 June 2018.

  29. Okafor I, Olatona F, Olufemi O. Breastfeeding practices of mothers of young children in Lagos. Nigeria Niger J Paediatr. 2014;41(1):43–7.

    Article  Google Scholar 

  30. Horii N, Guyon AB, Quinn VJ. Determinants of delayed initiation of breastfeeding in rural Ethiopia: programmatic implications. Food Nutr Bull. 2011;32(2):94–102.

    Article  Google Scholar 

  31. Patel A, Badhoniya N, Khadse S, Senarath U, Agho KE, Dibley MJ, et al. Infant and young child feeding indicators and determinants of poor feeding practices in India: secondary data analysis of National Family Health Survey 2005–06. Food Nutr Bull. 2010;31(2):314–33.

    Article  Google Scholar 

  32. Arora A, Manohar N, Hayen A, Bhole S, Eastwood J. Levy s, Scott JA. Determinants of breastfeeding initiation among mothers in Sydney, Australia: findings from a birth cohort study. Int Breastfeed J. 2017;12(1):39.

    Article  Google Scholar 

  33. Esteves TMB, Daumas RP, MICd O, CAdFd A, Leite IC. Factors associated to breastfeeding in the first hour of life: systematic review. Rev Saude Publica. 2014;48(4):697–708.

    Article  Google Scholar 

  34. Pérez-Escamilla R, Maulén-Radovan I, Dewey KG. The association between cesarean delivery and breast-feeding outcomes among Mexican women. Am J Public Health. 1996;86(6):832–6.

    Article  Google Scholar 

  35. Legesse M, Demena M, Mesfin F, Haile D. Prelacteal feeding practices and associated factors among mothers of children aged less than 24 months in Raya kobo district, north eastern Ethiopia: a cross-sectional study. Int Breastfeed J. 2014;9(1):189.

    Article  Google Scholar 

  36. Agho KE, Ogeleka P, Ogbo FA, Ezeh OK, Eastwood J, Page A. Trends and predictors of prelacteal feeding practices in Nigeria (2003–2013). Nutrients. 2016;8(8):462.

    Article  Google Scholar 

  37. Nguyen PH, Keithly SC, Nguyen NT, Nguyen TT, Tran LM, Hajeebhoy N. Prelacteal feeding practices in Vietnam: challenges and associated factors. BMC Public Health. 2013;13(1):932.

    Article  Google Scholar 

  38. Khanal V, Adhikari M, Sauer K, Zhao Y. Factors associated with the introduction of prelacteal feeds in Nepal: findings from the Nepal demographic and health survey 2011. Int Breastfeed J. 2013;8(1):9.

    Article  Google Scholar 

  39. Lessen R, Crivelli-Kovach A. Prediction of initiation and duration of breast-feeding for neonates admitted to the neonatal intensive care unit. J Perinat Neonatal Nurs. 2007;21(3):256–66.

    Article  Google Scholar 

  40. Mihrshahi S, Kabir I, Roy SK, Agho KE, Senarath U, Dibley MJ, et al. Determinants of infant and young child feeding practices in Bangladesh: secondary data analysis of demographic and health survey 2004. Food Nutr Bull. 2010;31(2):295–313.

    Article  Google Scholar 

Download references

Acknowledgements

We are grateful to Measure DHS, ICF International Rockville, Maryland, USA for providing the 2016 EDHS data for this analysis.

Funding

This study did not receive any funding from any organisation.

Availability of data and materials

The survey datasets used in this study was based on publicly available dataset that is freely available online with no participant’s identity from http://www.dhsprogram.com/data/available-datasets.cfm.

Approval was sought from MEASURE DHS/ICF International and permission was granted for this use.

Author information

Authors and Affiliations

  1. School of Nursing and Midwifery, Western Sydney University, Campbelltown, NSW, Australia

    James Rufus John

  2. Capital Markets Cooperative Research Centre, Sydney, Australia

    James Rufus John

  3. BRAC James P Grant School of Public Health, BRAC University, Dhaka, Bangladesh

    Sabuj Kanti Mistry

  4. University of Tasmania, Faculty of Health, School of Health Sciences, Launceston, Tasmania, Australia

    Getahun Kebede

  5. University of Gondar, College of Medicine and Health Sciences, Institute of Public Health, Gondar, Ethiopia

    Getahun Kebede

  6. School of Science and Health, Western Sydney University, Campbelltown, NSW, Australia

    Narendar Manohar & Amit Arora

  7. Translational Health Research Institute, Western Sydney University, Campbelltown, NSW, Australia

    Amit Arora

  8. Oral Health Services and Sydney Dental Hospital, Sydney Local Health District, Surry Hills, NSW, Australia

    Amit Arora

  9. Discipline of Child and Adolescent Health, Sydney Medical School, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia

    Amit Arora

Authors
  1. James Rufus John
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Sabuj Kanti Mistry
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Getahun Kebede
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Narendar Manohar
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Amit Arora
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

JRJ, AA, NM and GK were involved in formatting the research question. SKM performed the analysis with assistance from JRJ and AA. All authors prepared the initial draft of the manuscript. JRJ and AA critically revised the manuscript for intellectual content. All authors approved the final version of the manuscript.

Corresponding author

Correspondence to Amit Arora.

Ethics declarations

Ethics approval and consent to participate

This study is a secondary data analysis of the EDHS, which is publicly available, approval was sought from MEASURE DHS/ICF International and permission was granted for this use. The original DHS data were collected in conformity with international and national ethical guidelines. Ethical clearance was provided by the Ethiopian Public Health Institute (EPHI) (formerly the Ethiopian Health and Nutrition Research Institute (EHNRI) Review Board, the National Research Ethics Review Committee (NRERC) at the Ministry of Science and Technology, the Institutional Review Board of ICF International, and the United States Centers for Disease Control and Prevention (CDC). Written consent was obtained from mothers/caregivers and data were recorded anonymously at the time of data collection during the EDHS 2016.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

John, J.R., Mistry, S.K., Kebede, G. et al. Determinants of early initiation of breastfeeding in Ethiopia: a population-based study using the 2016 demographic and health survey data. BMC Pregnancy Childbirth 19, 69 (2019). https://0-doi-org.brum.beds.ac.uk/10.1186/s12884-019-2211-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://0-doi-org.brum.beds.ac.uk/10.1186/s12884-019-2211-0

Keywords

BMC Pregnancy and Childbirth

ISSN: 1471-2393

Contact us