Association of age and colostrum discarding with breast-feeding practice in Ethiopia: systematic review and meta-analyses

Sisay Mulugeta Alemu; Yihun Mulugeta Alemu; Tesfa Dejenie Habtewold

doi:10.1017/S1368980019000314

Association of age and colostrum discarding with breast-feeding practice in Ethiopia: systematic review and meta-analyses

Published online by Cambridge University Press: 08 March 2019

Sisay Mulugeta Alemu

Yihun Mulugeta Alemu and

Tesfa Dejenie Habtewold

Show author details

Sisay Mulugeta Alemu*: Affiliation:
Mental Health and Psychosocial Support Program, International Medical Corps, 2314 Dolo Ado, Ethiopia
Yihun Mulugeta Alemu: Affiliation:
Department of Public Health, Bahir Dar University, Bahir Dar, Ethiopia
Tesfa Dejenie Habtewold: Affiliation:
Department of Epidemiology, University of Groningen, Groningen, The Netherlands
*: *Corresponding author: Email [email protected]

Article contents

Abstract
Objective
Design
Setting
Participants
Result
Conclusions
Methods
Result
Discussion
Conclusion
References

Rights & Permissions

Abstract

Objective

To investigate whether maternal/caregiver’s age, infant age (0–6 months) and discarding colostrum affects timely initiation of breast-feeding (TIBF) and exclusive breast-feeding (EBF) in Ethiopia.

Design

A systematic search of PubMed, SCOPUS, EMBASE, CINHAL, Web of Science and WHO Global Health Library electronic databases was done for all articles published in English from 2000 to January 2018. Two reviewers independently screened, extracted and graded the quality of studies using Newcastle–Ottawa Scale. A weighted inverse-variance random-effects model meta-analysis, cumulative meta-analysis and mixed-effects meta-regression analysis were done.

Setting

All observational studies conducted in Ethiopia.

Participants

Mothers of children aged less than 2 years.

Result

A total of forty articles (fourteen studies on TIBF and twenty-six on EBF) were included. TIBF was associated with colostrum discarding (OR=0·38; 95 % CI 0·21, 0·68) but not with maternal/caregiver’s age (OR=0·98; 95 % CI 0·83, 1·15). In addition, colostrum discarding (OR=0·53; 95 % CI 0·36, 0·78) and infant age (OR=1·77; 95 % CI 1·38, 2·27) were significantly associated with EBF but not maternal/caregiver’s age (OR=1·09; 95 % CI 0·84, 1·41).

Conclusions

There was no association between maternal/caregiver’s age and breast-feeding practice (EBF and TIBF). Colostrum discarding was associated with both EBF and TIBF. This evidence could be helpful to counsel all mothers of reproductive age and who discard colostrum.

Keywords

Breast-feeding Maternal age Infant Review Meta-analysis Ethiopia

Type: Review Article
Information: Public Health Nutrition , Volume 22 , Issue 11 , August 2019 , pp. 2063 - 2082

DOI: https://doi.org/10.1017/S1368980019000314 [Opens in a new window]
Copyright: © The Authors 2019

The WHO and UNICEF define timely initiation of breast-feeding (TIBF) as putting a newborn to breast within 1 h of birth and exclusive breast-feeding (EBF) as feeding infants only human milk through breast-feeding or expressed breast milk and no other liquids or solids, except for drops or syrups with nutritional supplements or medicine⁽ ¹ ⁾. All infants should receive human milk within the first hour of birth, be exclusively breast-fed for the first 6 months and thereafter be introduced to nutritionally adequate and safe complementary foods with continued breast-feeding for at least 2 years⁽ ² ^, ³ ⁾. Breast-feeding is one of the most cost-effective interventions that prevents maternal and newborn morbidity and mortality⁽ ⁴ ^– Reference Patel, Bansal and Nimbalkar ⁷ ⁾. For example, TIBF and EBF prevent 22 and 60 % of neonatal deaths, respectively⁽ ² ^, Reference Edmond, Zandoh and Quigley ⁸ ^, ⁹ ⁾. Furthermore, EBF for a longer duration benefits child neurodevelopment and increases intelligence quotient⁽ Reference Belfort ¹⁰ ⁾.

Despite the aforementioned advantages, significantly low percentages of mothers initiate breast-feeding within the first hour of birth and maintain EBF for 6 months. Globally, 44 and 40 % of newborns are breast-fed within the first hour and breast-feed exclusively for 6 months, respectively⁽ ⁴ ^, ¹¹ ⁾. In developing countries, the prevalence of TIBF ranges from 22·4 to 52·8 %⁽ Reference Kitano, Nomura and Kido ¹² ^– Reference Lande, Andersen and Baerug ¹⁸ ⁾ and EBF prevalence ranges from 10·0 to 49·1 %⁽ ¹¹ ^, Reference Kitano, Nomura and Kido ¹² ^, Reference Ludvigsson and Ludvigsson ¹³ ^, Reference Dennis ¹⁹ ^, Reference Hruschka, Sellen and Stein ²⁰ ⁾. In Ethiopia, based on our previous meta-analyses⁽ Reference Habtewold, Mohammed and Endalamaw ²¹ ⁾, the national prevalence of TIBF and EBF is 66·5 and 60·1 %, respectively.

Previous studies have identified several associated factors of TIBF and EBF, including maternal/caregiver’s age, newborn age and colostrum discarding⁽ Reference Kitano, Nomura and Kido ¹² ^– Reference Lande, Andersen and Baerug ¹⁸ ^, Reference Fisher, Hammarberg and Wynter ²² ^– Reference Kaneko, Kaneita and Yokoyama ²⁵ ⁾. Previous studies show that infant age and colostrum discarding have been associated with late initiation of breast-feeding and non-exclusive breast-feeding⁽ Reference Senarath, Dibley and Agho ¹⁴ ^, Reference Victor, Baines and Agho ¹⁶ ^, Reference Nyanga, Musita and Otieno ²⁶ ^– Reference Legesse, Demena and Mesfin ²⁸ ⁾. Regarding maternal/caregiver’s age, most of the reviewed literature reveals that older mothers practise TIBF⁽ Reference Tarrant, Younger and Sheridan-Pereira ¹⁵ ^, Reference Victor, Baines and Agho ¹⁶ ^, Reference Dennis ¹⁹ ^, Reference Esteves, Daumas and Oliveira ²⁴ ⁾ and EBF⁽ Reference Ludvigsson and Ludvigsson ¹³ ^, Reference Lande, Andersen and Baerug ¹⁸ ^, Reference Hruschka, Sellen and Stein ²⁰ ^, Reference Fisher, Hammarberg and Wynter ²² ^, Reference Chye, Zain and Lim ²⁹ ⁾ at higher rates than young mothers, although the age cut-off value varies between studies. Another study⁽ Reference Amin, Hablas and Al Qader ²³ ⁾ which measured age as a continuous variable also concluded that increased maternal age is positively associated with TIBF and EBF. On the contrary, some studies showed that increased maternal age was associated with delayed initiation of breast-feeding and non-exclusive breast-feeding⁽ Reference Kitano, Nomura and Kido ¹² ^, Reference Kaneko, Kaneita and Yokoyama ²⁵ ⁾. Furthermore, other studies showed absence of an association⁽ Reference Meinzen-Derr, Guerrero and Altaye ¹⁷ ^, Reference Koosha, Hashemifesharaki and Mousavinasab ³⁰ ⁾. Taken together, inconsistencies persist and the association is inconclusive.

Hence, there is an urgent need to synthesize individual studies’ data to make a better conclusion on the association of maternal age, infant age and colostrum discarding with breast-feeding practice (i.e. TIBF and EBF). So far, several systematic reviews and meta-analyses have been conducted on TIBF and EBF⁽ Reference Senarath, Dibley and Agho ¹⁴ ^, Reference Victor, Baines and Agho ¹⁶ ^, Reference Esteves, Daumas and Oliveira ²⁴ ^, Reference Scott and Binns ³¹ ^– Reference Alebel, Dejenu and Mullu ³³ ⁾. In Ethiopia, there is a paucity of systematic review and meta-analysis with regard to associated factors of TIBF and EBF. The present meta-analyses and systematic review aimed to determine whether maternal/caregiver’s age, infant age and colostrum discharging affect TIBF and EBF in Ethiopia. We hypothesized that: (i) increased maternal age would be positively associated with breast-feeding practice due to accumulated experience; (ii) increased infant age would be negatively associated with EBF; and (iii) colostrum discarding would be negatively associated with breast-feeding practice.

Following international recommendations⁽ ² ⁾, the Ethiopian Government has taken steps to improve infant and young child feeding practices. Several national nutritional strategies⁽ ³⁴ ⁾, guidelines⁽ ³⁵ ⁾ and nutrition programmes⁽ ³⁶ ^, ³⁷ ⁾ have been developed by Ministry of Health of Ethiopia since 2004. Likewise, the Health Sector Transformation Plan of Ethiopia⁽ ³⁸ ⁾ has a target to increase EBF to 72 % by 2020. Furthermore, Ethiopia has recently started celebrating World Breastfeeding Week every year⁽ ³⁹ ⁾. However, TIBF and EBF coverages are still below the very good rating of WHO, which is 90 % or above⁽ ⁴⁰ ⁾. This can be attributed to several factors including colostrum discarding. It is also linked to infant as well as maternal/caregiver’s age⁽ Reference Ludvigsson and Ludvigsson ¹³ ^– Reference Victor, Baines and Agho ¹⁶ ^, Reference Lande, Andersen and Baerug ¹⁸ ^– Reference Hruschka, Sellen and Stein ²⁰ ^, Reference Fisher, Hammarberg and Wynter ²² ^– Reference Esteves, Daumas and Oliveira ²⁴ ^, Reference Nyanga, Musita and Otieno ²⁶ ^– Reference Chye, Zain and Lim ²⁹ ⁾. This meta-analysis information could be valuable to provide updated evidence to develop national guidelines and strategies, including on colostrum discarding.

Methods

Protocol registration and publication

The protocol has been registered with the University of York Centre for Reviews and Dissemination’s international prospective register of systematic reviews (PROSPERO; http://www.crd.york.ac.uk/PROSPERO/display_record.asp?ID=CRD42017056768) and published⁽ Reference Habtewold, Islam and Sharew ⁴¹ ⁾.

Data source and search strategy

For all available publications, systematic searchs of PubMed, SCOPUS, EMBASE, Cumulative Index to Nursing and Allied Health Literature (CINAHL), Web of Science and WHO Global Health Library electronic databases was done. In addition, bibliographies of identified articles and grey literatures were hand-searched. A comprehensive search strategy was developed for each database in consultation with a medical information specialist (see online supplementary material, Supplemental File 1).

Eligibility criteria

All observational studies (cross-sectional, case–control, cohort, survey and surveillance reports) conducted in Ethiopia, published in English from 2000 to January 2018, were included. This period was selected because population demography changes over time and we wanted to include the latest evidences in the country. In addition, most of the published studies on the topic were conducted in this period. However, studies on preterm infants, infants in a neonatal intensive care unit or a special care baby unit, and low-birth-weight infants were excluded. Mothers or infants with HIV/AIDS were also excluded because health-care workers provide breast-feeding counselling and related interventions due to WHO recommendations on HIV and infant feeding. Consequently, the level of EBF in mothers or infants with HIV/AIDS may be higher and the associated factors may not be the same as those of HIV-uninfected mothers. Further, commentaries, anonymous reports, letters, duplicate studies, editorials, qualitative studies and citations without full text were excluded.

Study screening and selection

All studies obtained from databases and manual search were exported to EndNote citation manager. The title and abstract of all studies were screened by two reviewers (S.M.A. and T.D.H.) independently. Agreement between the reviewers, as measured by Cohen’s κ, was 0·76. Any disagreement was resolved by discussion. When consensus could not be reached, a third reviewer, who also had expertise in this area, approved the final list of retained studies. A full-text review was performed by two independent investigators (S.M.A. and T.D.H.).

Quality assessment and data extraction

The Newcastle–Ottawa Scale, which has good inter-rater reliability and validity, was used to assess the quality of studies and for potential publication bias⁽ Reference Hartling, Hamm and Milne ⁴² ^, Reference Hootman, Driban and Sitler ⁴³ ⁾. The Newcastle–Ottawa Scale includes three categorical criteria with a maximum score of 9: a maximum of four stars are allotted for ‘selection’; a maximum of two stars are allotted for ‘comparability’; and a maximum of three stars are allotted for ‘outcome’. The quality of each study was rated using the following scoring algorithm: ≥7, ‘good’; 2–6, ‘fair’; and ≤1, ‘poor’⁽ Reference McPheeters, Kripalani and Peterson ⁴⁴ ⁾. Only studies of ‘good’ quality were selected for the final review and analysis.

In addition, to define outcome measurements, the WHO infant and young child feeding practice guideline was strictly followed. TIBF was assessed by ‘since birth’, while EBF was assessed in one of the following ways: 24 h recall/seven repeated 24 h recalls/6-month recalling method/7 d self-recall/since birth dietary recall method. Based on previous systematic review reports⁽ Reference Esteves, Daumas and Oliveira ²⁴ ^, Reference Boccolini, Carvalho and Oliveira ⁴⁵ ^, Reference Sharma and Byrne ⁴⁶ ⁾, maternal/caregiver’s age was dichotomized as ≥25 v. <25 years old whereas infant age was dichotomized as ≤3 v. 3–6 months. The Joanna Briggs Institute tool⁽ Reference Munn, Tufanaru and Aromataris ⁴⁷ ⁾ was used to extract the following data: study area (region and place), method (design), population, number of mothers (calculated sample size and participated in actual study) and cross-tabulated data. Geographic regions were categorized based on the current Federal Democratic Republic of Ethiopia administrative structure. Discrepancies were resolved by consensus and cross-checking with the full text.

Statistical analysis

A weighted inverse-variance random-effects model meta-analyses was implemented. In addition, to illustrate the trend of evidence regarding the effect of newborn gender, antenatal clinic and postnatal clinic attendance on breast-feeding practices, a cumulative meta-analysis was done. Publication bias was assessed by visual inspection of the funnel plot and Egger’s regression test for funnel plot asymmetry using se as a predictor in a mixed-effects meta-regression model at P value threshold of ≤0·01⁽ Reference Egger, Smith and Schneider ⁴⁸ ⁾. The Duval and Tweedie trim-and-fill method⁽ Reference Duval and Tweedie ⁴⁹ ⁾ was used if we found an asymmetric funnel plot, which indicates publication bias. Cochran’s Q χ ² test, τ ² and I ² statistics were used to test for heterogeneity, estimate the amount of total/residual heterogeneity and measure the variability attributed to heterogeneity, respectively⁽ Reference Higgins and Thompson ⁵⁰ ⁾; for the current meta-analysis, we used a reference value of I ²>80 % to indicate substantial variability related to heterogeneity⁽ Reference Habtewold, Islam and Sharew ⁴¹ ⁾. Mixed-effects meta-regression analysis was done to identify possible sources of between-study heterogeneity. The data were analysed using ‘metaphor’ packages in R software version 3.2.1 for Windows⁽ Reference Viechtbauer ⁵¹ ⁾.

Data synthesis and reporting

We analysed the data in two groups of outcome measurements: TIBF and EBF. Results for each variable are shown using forest plots. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline was strictly followed (see online supplementary material, Supplemental File 2).

Minor changes from the published protocol

Before analysis was done, we made the following changes to our methods from the published protocol⁽ Reference Habtewold, Islam and Sharew ⁴¹ ⁾. We added the Joanna Briggs Institute tool⁽ Reference Munn, Tufanaru and Aromataris ⁴⁷ ⁾ to extract the data. In addition, we used the Duval and Tweedie trim-and-fill method⁽ Reference Duval and Tweedie ⁴⁹ ⁾ to manage publication bias. Furthermore, cumulative meta-analysis and mixed-effects meta-regression analysis were done to reveal the trend of evidence on each associated factor and to identify possible sources of between-study heterogeneity, respectively.

Result

Search results

We obtained 169 articles from PubMed, twenty-four from EMBASE, 200 from Web of Science, eighty-five from SCOPUS and five from other (CINHAL and WHO Global Health Library) electronic database searching. Fifty-one additional articles were found through a manual search of reference lists of included articles. After removing duplicates and screening of titles and abstracts, the full texts of eighty-five studies were reviewed to assess eligibility. Forty-five articles were excluded after a full-text review due to several reasons: nineteen studies on complementary feeding, three on pre-lacteal feeding, three on malnutrition, nineteen with different variables of interest and one project review report. As a result, forty articles (i.e. fourteen studies on TIBF and twenty-six on EBF) fulfilled the inclusion criteria and were included in the meta-analyses. The PRISMA flow diagram of the literature screening and selection process is shown in Fig. 1.

Fig. 1 Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flow diagram of the literature screening and selection process for studies included in the present systematic review and meta-analysis on factors affecting timely initiation of breast-feeding (TIBF) and exclusive breast-feeding (EBF) in Ethiopia. Note ‘n’ in each stage represents the total number of studies that fulfilled a particular criterion

Study characteristics

Of the fourteen studies on TIBF, most were conducted in the Southern Nations, Nationalities and Peoples’ Region (SNNPR) and Oromia region. Regarding maternal/caregiver’s residence, six of the studies were conducted among urban dwellers (Table 1).

Table 1 Characteristics of studies included in the present systematic review and meta-analysis on factors affecting timely initiation of breast-feeding (TIBF) in Ethiopia

SNNPR, Southern Nations, Nationalities and Peoples’ Region.

The majority of the twenty-six studies on EBF were done in Amhara and SNNPR regions with eight and seven studies, respectively. Furthermore, two studies used nationally representative data of the Ethiopian Demographic and Health Survey (EDHS). Likewise, nearly half of the studies were conducted in urban residents (Table 2).

Table 2 Characteristics of studies included in the present systematic review and meta-analysis on factors affecting exclusive breast-feeding (EBF) in Ethiopia

SNNPR, Southern Nations, Nationalities and Peoples’ Region; EDHS, Ethiopian Demographic and Health Survey.

Timely initiation of breast-feeding

Among the fourteen studies, ten studies⁽ Reference Wolde, Birhanu and Ejeta ⁵² ^– Reference Ekubay, Berhe and Yisma ⁶¹ ⁾ reported the association between TIBF and maternal/caregiver’s age in 4963 mothers. The pooled OR of maternal/caregiver’s age was 0·98 (95 % CI 0·83, 1·15, P=0·78; Fig. 2). Although not statistically significant, mothers aged ≥25 years had 2 % lower chance of initiating breast-feeding within 1 h of birth compared with their younger counterparts. Egger’s regression test for funnel plot asymmetry was not significant (z=−0·40, P=0·69; see online supplementary material, Supplemental Fig. 1).

Fig. 2 Forest plot of ten studies on the association of maternal/caregiver’s age with timely initiation of breast-feeding (TIBF) in Ethiopia. The study-specific OR and 95 % CI are represented by the black square and horizontal line, respectively, with area of the square proportional to the specific-study weight to the overall meta-analysis. The centre of the black diamond represents the pooled OR and its width represents the pooled 95 % CI (LIBF, late initiation of breast-feeding; REM, random-effects model)

Likewise, six out of fourteen studies reported the association between TIBF and colostrum discarding in 2305 mothers⁽ Reference Wolde, Birhanu and Ejeta ⁵² ^, Reference Adugna ⁵⁴ ^, Reference Hailemariam, Adeba and Sufa ⁶² ^– Reference Liben and Yesuf ⁶⁵ ⁾. The pooled OR of colostrum discarding was found to be 0·38 (95 % CI 0·21, 0·68, P=0·001; Fig. 3). Compared with mothers who feed colostrum, mothers who discard colostrum had 62 % significantly lower chance of initiating breast-feeding within 1 h. Egger’s regression test for funnel plot asymmetry was not significant (z=−0·24, P=0·81; see online supplementary material, Supplemental Fig. 2).

Fig. 3 Forest plot of six studies on the association of colostrum discarding with timely initiation of breast-feeding (TIBF) in Ethiopia. The study-specific OR and 95 % CI are represented by the black square and horizontal line, respectively, with area of the square proportional to the specific-study weight to the overall meta-analysis. The centre of the black diamond represents the pooled OR and its width represents the pooled 95 % CI (D, discarding; NotD, not discarding; LIBF, late initiation of breast-feeding; REM, random-effects model)

Exclusive breast-feeding

Thirteen studies⁽ Reference Alemayehu, Abreha and Yebyo ⁵⁶ ^, Reference Berhe, Mekonnen and Bayray ⁵⁷ ^, Reference Regassa ⁶⁰ ^, Reference Abera ⁶⁶ ^– Reference Sefene, Birhanu and Awoke ⁷⁵ ⁾ involving 4929 individuals reported the association between EBF and maternal/caregiver’s age. As shown in Fig. 4, the pooled OR of maternal/caregiver’s age was 1·09 (95 % CI 0·84, 1·41, P=0·51). Mothers aged ≥25 years had 9 % higher chance of EBF during the first 6 months compared with mothers <25 years old; however, it was not statistically significant. Egger’s regression test for funnel plot asymmetry was not significant (z=−0·60, P=0·55; see online supplementary material, Supplemental Fig. 3).

Fig. 4 Forest plot of thirteen studies on the association of maternal/caregiver’s age with exclusive breast-feeding (EBF) in Ethiopia. The study-specific OR and 95 % CI are represented by the black square and horizontal line, respectively, with area of the square proportional to the specific-study weight to the overall meta-analysis. The centre of the black diamond represents the pooled OR and its width represents the pooled 95 % CI (NEBF, non-exclusive breast-feeding; REM, random-effects model)

In addition, eleven⁽ Reference Berhe, Mekonnen and Bayray ⁵⁷ ^, Reference Setegn, Belachew and Gerbaba ⁷¹ ^, Reference Sonko and Worku ⁷² ^, Reference Alemayehu, Haidar and Habte ⁷⁶ ^– Reference Elyas, Mekasha and Admasie ⁸³ ⁾ out of twenty-six studies reported the association between EBF and infant age with a total sample of 6881 mothers. The pooled OR of infant age was 1·77 (95 % CI 1·38, 2·27, P=0·001; Fig. 5). Children aged ≤3 months had 77 % statistically significant higher chance of being exclusively breast-fed compared with children >3 months old. Egger’s regression test for funnel plot asymmetry was not significant (z=0·82, P=0·41; see online supplementary material, Supplemental Fig. 4).

Fig. 5 Forest plot of eleven studies on the association of infant age with exclusive breast-feeding (EBF) in Ethiopia. The study-specific OR and 95 % CI are represented by the black square and horizontal line, respectively, with area of the square proportional to the specific-study weight to the overall meta-analysis. The centre of the black diamond represents the pooled OR and its width represents the pooled 95 % CI (NEBF, non-exclusive breast-feeding; REM, random effects model)

Finally, thirteen studies⁽ Reference Alemayehu, Abreha and Yebyo ⁵⁶ ^, Reference Tamiru and Tamrat ⁵⁹ ^, Reference Lenja, Demissie and Yohannes ⁷⁰ ^, Reference Teka, Assefa and Haileslassie ⁷⁴ ^, Reference Liben, Gemechu and Adugnew ⁷⁸ ^– Reference Arage and Gedamu ⁸² ^, Reference Egata, Berhane and Worku ⁸⁴ ^– Reference Echamo ⁸⁷ ⁾ reported the association between EBF and colostrum discarding with a sample of 6803 mothers. As indicated in Fig. 6, the pooled OR of colostrum discarding was 0·53 (95 % CI 0·36, 0·78, P<0·001). Mothers who discard colostrum had 47 % statistically significant lower chance of EBF during the first 6 months compared with mothers who feed colostrum. Egger’s regression test for funnel plot asymmetry was not significant (z=0·84, P=0·40; see online supplementary material, Supplemental Fig. 5).

Fig. 6 Forest plot of thirteen studies on the association of discarding colostrum with exclusive breast-feeding (EBF) in Ethiopia. The study-specific OR and 95 % CI are represented by the black square and horizontal line, respectively, with area of the square proportional to the specific-study weight to the overall meta-analysis. The centre of the black diamond represents the pooled OR and its width represents the pooled 95 % CI (D, discarding; NotD, not discarding; NEBF, non-exclusive breast-feeding; REM, random-effects model)

Cumulative meta-analysis

As illustrated in Fig. 7, the effect of increased maternal age on TIBF has been increasing slowly over time whereas the effect of discarding colostrum (Fig. 8) has been increasing dramatically. Similarly, the effect of maternal age (Fig. 9), discarding colostrum (Fig. 10) and infant age (Fig. 11) on EBF has been increasing.

Fig. 7 Forest plot showing the results from a cumulative meta-analysis of studies examining the effect of maternal age on timely initiation of breast-feeding in Ethiopia. The study-specific (first data point)/cumulative OR and 95 % CI are represented by the black square and horizontal line, respectively

Fig. 8 Forest plot showing the results from a cumulative meta-analysis of studies examining the effect of discarding colostrum on timely initiation of breast-feeding in Ethiopia. The study-specific (first data point)/cumulative OR and 95 % CI are represented by the black square and horizontal line, respectively

Fig. 9 Forest plot showing the results from a cumulative meta-analysis of studies examining the effect of maternal age on exclusive breast-feeding in Ethiopia. The study-specific (first data point)/cumulative OR and 95 % CI are represented by the black square and horizontal line, respectively

Fig. 10 Forest plot showing the results from a cumulative meta-analysis of studies examining the effect of discarding colostrum on exclusive breast-feeding in Ethiopia. The study-specific (first data point)/cumulative OR and 95 % CI are represented by the black square and horizontal line, respectively

Fig. 11 Forest plot showing the results from a cumulative meta-analysis of studies examining the effect of infant age on exclusive breast-feeding in Ethiopia. The study-specific (first data point)/cumulative OR and 95 % CI are represented by the black square and horizontal line, respectively

Meta-regression analysis

In studies reporting the association between TIBF and discarding colostrum, 95 % of the heterogeneity was due to variation in study area (region), residence of mothers, sample size and publication year. Based on the omnibus test, however, none of these factors influenced their association (QM=6·46, df=7, P=0·49; Table 3). In studies reporting the association between TIBF and maternal age, there was no statistically significant heterogeneity between studies (τ ²=2 %, Q=12·30, df=9, P=0·20); as a result, it is not relevant to investigate the possible reasons for heterogeneity.

Table 3 Meta-regression analysis to identify possible reasons for between-study heterogeneity in studies included in the present systematic review and meta-analysis on factors affecting timely initiation of breast-feeding (TIBF) and exclusive breast-feeding (EBF) in Ethiopia

SNNPR, Southern Nations, Nationalities and Peoples’ Region.

* Since we do not have a specific hypothesis, the reference category is selected arbitrarily.

† Residence is dropped from the model due to small sample size of included studies.

In EBF, 100·0, 88·2 and 51·1 % of the heterogeneity among studies reporting maternal age, infant age and discarding colostrum was due to variation in study area (region), residence of mothers, sample size and publication year, respectively. Based on the omnibus test, study area (region), publication year and sample size significantly influenced the association between maternal age and EBF practice (QM=42·27, df=9, P<0·001). Study area (region) and publication year also significantly influenced the association between infant age and EBF practice (QM=27·24, df=8, P=0·0006). Furthermore, residence and publication year significantly influenced the association between discarding colostrum and EBF (QM=16·66, df=8, P=0·03; Table 3).

Discussion

The present study examined the associations of TIBF and EBF with colostrum discarding, maternal/caregiver’s age and infant age. To our knowledge, our study is the first systematic review and meta-analysis on this topic in Ethiopia to date. The meta-analysis uncovered that colostrum discarding was significantly associated with TIBF but not maternal/caregiver’s age. On the other hand, colostrum discarding and infant age were found to be significantly associated with EBF but not maternal/caregiver’s age.

We found that mothers who discard colostrum had 62 % significantly lower chance of initiating breast-feeding within 1 h compared with mothers who feed colostrum to their child. This may be explained by the attempt of discarding colostrum to get white milk taking time, which therefore results in a delayed initiation of breast-feeding.

In the present meta-analysis, we found a statistically significant association between EBF and infant age. This finding confirmed our hypothesis and is consistent with a large body of evidence showing that increased infant age is negatively associated with EBF⁽ Reference Senarath, Dibley and Agho ¹⁴ ^, Reference Victor, Baines and Agho ¹⁶ ^, Reference Nyanga, Musita and Otieno ²⁶ ^, Reference Patel, Badhoniya and Khadse ²⁷ ^, Reference Dorgham, Hafez and Kamhawy ⁸⁸ ^, Reference Agho, Dibley and Odiase ⁸⁹ ⁾. This may be due to the fact that giving traditional postpartum care and support is common in Ethiopia immediately after birth, which may create opportunity for the mother to exclusively breast-feed the child. Since this traditional postpartum care and support decreases as the age of the infant increases, it may lead the mother to work outside. This may therefore force the mother to stop EBF. Evidence worldwide also agrees on the point that presence of social support is associated with better breast-feeding outcome⁽ Reference Kanhadilok and McGrath ⁹⁰ ^– Reference Kavle, LaCroix and Dau ⁹³ ⁾. Another possible reason is the workload and short maternity leave in Ethiopia, only two months postpartum until recently, which may influence the mother to withdraw EBF early. This hypothesis is supported by our previous meta-analyses⁽ Reference Habtewold, Mohammed and Endalamaw ²¹ ⁾, whereby maternal employment significantly lowered EBF, and other studies⁽ Reference Balogun, Dagvadorj and Anigo ⁹² ^– Reference Ogbo, Eastwood and Page ⁹⁵ ⁾. Moreover, this could also be related to the short birth interval in Ethiopia.

We noted that colostrum discarding was significantly associated with EBF. The finding was in line with studies conducted in Nepal⁽ Reference Chandrashekhar, Joshi and Binu ⁹⁶ ⁾ and Laos⁽ Reference Barennes, Empis and Quang ⁹⁷ ⁾. This may be due to the fact that discarding colostrum leads to pre-lacteal feeding. In agreement with recent studies⁽ Reference Radwan ⁹⁸ ^– Reference Pandey, Tiwari and Senarath ¹⁰³ ⁾, maternal/caregiver’s age was not significantly associated with either EBF or TIBF. This is against our hypothesis and disproves the notion that older mothers have better breast-feeding experience than young mothers that helps them to practise optimal TIBF and EBF. However, there is robust evidence that, if supported, all reproductive-age mothers can maintain optimal TIBF and EBF equally⁽ Reference Patel, Badhoniya and Khadse ²⁷ ^, Reference Pereira-Santos, Santana and Oliveira ⁹⁴ ^, Reference Perera, Ranathunga and Fernando ¹⁰⁴ ⁾. Therefore, the discrepancy may be due to the following reasons: (i) most studies used maternal age rather than age at first birth; (ii) different studies have used different age categories; and (iii) breast-feeding is not age dependent or can be confounded by innate maternal behaviour.

The present meta-analyses study has several implications. It provided evidence on breast-feeding practice and its associated factors in an Ethiopian context, which can be useful for cross-country/cross-cultural comparison and for breast-feeding improvement initiatives in Ethiopia. The present study provides an overview of up-to-date evidence for nutritionists and public health professionals. The findings also indicate emphasis should be given for all age groups of mothers/caregivers during breast-feeding intervention. Furthermore, the study points out that colostrum discarding and associated beliefs should be considered during designing breast-feeding interventions.

The association was estimated in a large sample size and recent and nationally representative studies were included. In addition, the present systematic review and meta-analysis was conducted based on a registered and published protocol, and guidelines for the Meta-analysis of Observational Studies in Epidemiology (MOOSE) were strictly followed. The study has also several limitations. First, some studies were excluded because of the difference in age category. Second, almost all included studies were observational, which hinders inference of causality. Third, even though we used broad search strategies, the possibility of missing relevant studies cannot be fully exempted. Fourth, based on the conventional methods of statistical testing, a few analyses suffered from high levels of between-study heterogeneity. The cause of the heterogeneity was carefully explored and may be due to differences in study area; therefore, the result should be interpreted with caution.

Conclusion

In conclusion, colostrum discarding was a possible barrier for both TIBF and EBF. Additionally, increased infant age was found to be a risk factor for non-EBF. However, maternal/caregiver’s age was not a determinant factor for both TIBF and EBF. Interventions targeted on increasing the rate of TIBF and EBF should give special focus on colostrum discarding. In addition, future research is required to identify other factors affecting duration of EBF in Ethiopia. Further investigation is also required to assess the effect of age at first birth.

Acknowledgements

Acknowledgements: The authors’ special gratitude goes to Sjoukje van der Werf (University of Groningen, the Netherlands) for her support developing the search strings and Balewgizie Sileshi (University of Groningen, the Netherlands) for his support during title and abstract screening. Financial support: This study received no specific grant from any funding agency in the public, commercial or not-for-profit sectors. Conflict of interest: None declared. Authorship: T.D.H. and S.M.A. conceived of and designed the study. T.D.H. developed syntax for searching databases and analysed the data. T.D.H. and S.M.A. wrote and revised the manuscript. All authors read the submitted manuscript and gave final approval. Ethics of human subject participation: Not applicable.

Supplementary material

To view supplementary material for this article, please visit https://doi.org/10.1017/S1368980019000314

References

1. World Health Organization (2008) 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, USA. Geneva: WHO.Google Scholar

2. World Health Organization (2003) Global Strategy for Infant and Young Child Feeding. Geneva: WHO.Google Scholar

3. World Health Organization (2003) Complementary Feeding: Report of the Global Consultation, and Summary of Guiding Principles for Complementary Feeding of the Breastfed Child. Geneva: WHO.Google Scholar

4. UNICEF & World Health Organization (2017) Global Breastfeeding Scorecard, 2017: Tracking Progress for Breastfeeding Policies and Programmes. https://www.who.int/nutrition/publications/infantfeeding/global-bf-scorecard-2017-methology.pdf?ua=1 (accessed February 2019).Google Scholar

5. Ip, S, Chung, M, Raman, G et al. (2007) Breastfeeding and maternal and infant health outcomes in developed countries. Evid Technol Asses (Full Rep) issue 153, 1–186.Google Scholar

6. Islam, M, Rahman, S, Kamruzzaman, MI et al. (2013) Effect of maternal status and breastfeeding practices on infant nutritional status – a cross sectional study in the south-west region of Bangladesh. Pan Afr Med J 16, 139.Google Scholar

7. Patel, DV, Bansal, SC, Nimbalkar, AS et al. (2015) Breastfeeding practices, demographic variables, and their association with morbidities in children. Adv Prev Med 2015, 892825.Google Scholar

8. Edmond, KM, Zandoh, C, Quigley, MA et al. (2006) Delayed breastfeeding initiation increases risk of neonatal mortality. Pediatrics 117, e380–e386.Google Scholar

9. UNICEF (2007) The State of the World’s Children 2008: Child Survival. New York: UNICEF.Google Scholar

10. Belfort, MB (2017) The science of breastfeeding and brain development. Breastfeed Med 12, 459–461.Google Scholar

11. UNICEF (2016) Infant and young child feeding: Global Database. https://data.unicef.org/topic/nutrition/infant-and-young-child-feeding/ (accessed September 2018).Google Scholar

12. Kitano, N, Nomura, K, Kido, M et al. (2016) Combined effects of maternal age and parity on successful initiation of exclusive breastfeeding. Prev Med Rep 3, 121–126.Google Scholar

13. Ludvigsson, JF & Ludvigsson, J (2005) Socio‐economic determinants, maternal smoking and coffee consumption, and exclusive breastfeeding in 10 205 children. Acta Paediatr 94, 1310–1319.Google Scholar

14. Senarath, U, Dibley, MJ & Agho, KE (2010) Factors associated with nonexclusive breastfeeding in 5 east and southeast Asian countries: a multilevel analysis. J Hum Lact 26, 248–257.Google Scholar

15. Tarrant, RC, Younger, KM, Sheridan-Pereira, M et al. (2010) The prevalence and determinants of breast-feeding initiation and duration in a sample of women in Ireland. Public Health Nutr 13, 760–770.Google Scholar

16. Victor, R, Baines, SK, Agho, KE et al. (2013) Determinants of breastfeeding indicators among children less than 24 months of age in Tanzania: a secondary analysis of the 2010 Tanzania Demographic and Health Survey. BMJ Open 3, e001529.Google Scholar

17. Meinzen-Derr, JK, Guerrero, ML, Altaye, M et al. (2006) Risk of infant anemia is associated with exclusive breast-feeding and maternal anemia in a Mexican cohort. J Nutr 136, 452–458.Google Scholar

18. Lande, B, Andersen, L, Baerug, A et al. (2003) Infant feeding practices and associated factors in the first six months of life: the Norwegian infant nutrition survey. Acta Paediatr 92, 152–161.Google Scholar

19. Dennis, CL (2002) Breastfeeding initiation and duration: a 1990–2000 literature review. J Obstet Gynecol Neonatal Nurs 31, 12–32.Google Scholar

20. Hruschka, DJ, Sellen, DW, Stein, AD et al. (2003) Delayed onset of lactation and risk of ending full breast-feeding early in rural Guatemala. J Nutr 133, 2592–2599.Google Scholar

21. Habtewold, TD, Mohammed, SH, Endalamaw, A et al. (2018) Breast and complementary feeding in Ethiopia: new national evidence from systematic review and meta-analyses of studies in the past 10 years. Eur J Nutr. Published online: 18 September 2018. doi: 10.1007/s00394-018-1817-8.Google Scholar

22. Fisher, J, Hammarberg, K, Wynter, K et al. (2013) Assisted conception, maternal age and breastfeeding: an Australian cohort study. Acta Paediatr 102, 970–976.Google Scholar

23. Amin, T, Hablas, H & Al Qader, AA (2011) Determinants of initiation and exclusivity of breastfeeding in Al Hassa, Saudi Arabia. Breastfeed Med 6, 59–68.Google Scholar

24. Esteves, TMB, Daumas, RP, Oliveira, MICd et al. (2014) Factors associated to breastfeeding in the first hour of life: systematic review. Rev Saude Publica 48, 697–708.Google Scholar

25. Kaneko, A, Kaneita, Y, Yokoyama, E et al. (2006) Factors associated with exclusive breast-feeding in Japan: for activities to support child-rearing with breast-feeding. J Epidemiol 16, 57–63.Google Scholar

26. Nyanga, NM, Musita, C, Otieno, A et al. (2012) Factors influencing knowledge and practice of exclusive breastfeeding in Nyando district, Kenya. Afr J Food Agric Nutr Dev 12, issue 6; available at https://www.ajol.info/index.php/ajfand/article/view/82781 Google Scholar

27. Patel, A, Badhoniya, N, Khadse, S et al. (2010) 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 31, 314–333.Google Scholar

28. Legesse, M, Demena, M, Mesfin, F et al. (2015) Factors associated with colostrum avoidance among mothers of children aged less than 24 months in Raya Kobo district, north-eastern Ethiopia: community-based cross-sectional study. J Trop Pediatr 61, 357–363.Google Scholar

29. Chye, JK, Zain, Z, Lim, WL et al. (1997) Breastfeeding at 6 weeks and predictive factors. J Trop Pediatr 43, 287–292.Google Scholar

30. Koosha, A, Hashemifesharaki, R & Mousavinasab, N (2008) Breast-feeding patterns and factors determining exclusive breast-feeding. Singapore Med J 49, 1002–1006.Google Scholar

31. Scott, JA & Binns, CW (1999) Factors associated with the initiation and duration of breastfeeding: a review of the literature. Breastfeed Rev 7, 5–16.Google Scholar

32. Takahashi, K, Ganchimeg, T, Ota, E et al. (2017) Prevalence of early initiation of breastfeeding and determinants of delayed initiation of breastfeeding: secondary analysis of the WHO Global Survey. Sci Rep 7, 44868.Google Scholar

33. Alebel, A, Dejenu, G, Mullu, G et al. (2017) Timely initiation of breastfeeding and its association with birth place in Ethiopia: a systematic review and meta-analysis. Int Breastfeed J 12, 44.Google Scholar

34. Federal Ministry of Health, Family Health Department, Ethiopia (2004) National Strategy for Infant and Young Child Feeding, p. 21. https://extranet.who.int/nutrition/gina/sites/default/files/ETH%202004%20National%20Strategy%20for%20Infant%20and%20Young%20Child%20Feeding.pdf (accessed February 2019).Google Scholar

35. Federal Democratic Republic of Ethiopia (2016) National Guideline on Adolescent, Maternal, Infant and Young Child Nutrition. Addis Ababa: Ministry of Health.Google Scholar

36. Federal Democratic Republic of Ethiopia (2016) National Nutrition Program 2016–2020. Addis Ababa: Ministry of Health.Google Scholar

37. Federal Democratic Republic of Ethiopia (2013) National Nutrition Programme June 2013–June 2015. Addis Ababa: Ministry of Health.Google Scholar

38. Federal Democratic Republic of Ethiopia (2015) Health Sector Transformation Plan 2015/16–2019/2020 (2008–2012 EFY). Addis Ababa: Ministry of Health.Google Scholar

39. UNICEF (2009) News Note: World Breastfeeding Week CELEBRATED in Ethiopia. https://www.unicef.org/media/media_50700.html (accessed February 2019).Google Scholar

40. World Health Organization & LINKAGES (2003) Infant and Young Child Feeding: A Tool for Assessing National Practices, Policies and Programmes. Geneva: WHO.Google Scholar

41. Habtewold, TD, Islam, MA, Sharew, NT et al. (2017) SystEmatic review and meta-aNAlysis of infanT and young child feeding Practices (ENAT-P) in Ethiopia: protocol. BMJ Open 7, e017437.Google Scholar

42. Hartling, L, Hamm, M, Milne, A et al. (2012) Validity and Inter-Rater Reliability Testing of Quality Assessment Instruments. Rockville, MD: Agency for Healthcare Research and Quality.Google Scholar

43. Hootman, JM, Driban, JB, Sitler, MR et al. (2011) Reliability and validity of three quality rating instruments for systematic reviews of observational studies. Res Synth Methods 2, 110–118.Google Scholar

44. McPheeters, ML, Kripalani, S, Peterson, NB et al. (2012) Closing the quality gap: revisiting the state of the science (vol. 3: quality improvement interventions to address health disparities). Evid Rep Technol Assess (Full Rep) issue 208:3, 1–475.Google Scholar

45. Boccolini, CS, Carvalho, ML & Oliveira, MI (2015) Factors associated with exclusive breastfeeding in the first six months of life in Brazil: a systematic review. Rev Saude Publica 49, 91.Google Scholar

46. Sharma, IK & Byrne, A (2016) Early initiation of breastfeeding: a systematic literature review of factors and barriers in South Asia. Int Breastfeed J 11, 17.Google Scholar

47. Munn, Z, Tufanaru, C & Aromataris, E (2014) JBI’s systematic reviews: data extraction and synthesis. Am J Nurs 114, 49–54.Google Scholar

48. Egger, M, Smith, GD, Schneider, M et al. (1997) Bias in meta-analysis detected by a simple, graphical test. BMJ 315, 629–634.Google Scholar

49. Duval, S & Tweedie, R (2000) Trim and fill: a simple funnel‐plot-based method of testing and adjusting for publication bias in meta‐analysis. Biometrics 56, 455–463.Google Scholar

50. Higgins, J & Thompson, SG (2002) Quantifying heterogeneity in a meta‐analysis. Stat Med 21, 1539–1558.Google Scholar

51. Viechtbauer, W (2010) Conducting meta-analyses in R with the metafor package. J Stat Softw 36, 48.Google Scholar

52. Wolde, T, Birhanu, T & Ejeta, E (2014) Prevalence and determinants of timely initiation of breastfeeding among lactating mothers of urban dwellers in Western Ethiopia: a community based cross sectional study. Food Sci Qual Manage 31, 110–116.Google Scholar

53. Woldemichael, B & Kibie, Y (2016) Timely initiation of breastfeeding and its associated factors among mothers in Tiyo Woreda, Arsi Zone, Ethiopia: a community-based cross sectional study. Clinics Mother Child Health 13, 2.Google Scholar

54. Adugna, DT (2014) Women’s perception and risk factors for delayed initiation of breastfeeding in Arba Minch Zuria, Southern Ethiopia. Int Breastfeed J 9, 8.Google Scholar

55. Beyene, MG, Geda, NR, Habtewold, TD et al. (2017) Early initiation of breastfeeding among mothers of children under the age of 24 months in Southern Ethiopia. Int Breastfeed J 12, 1.Google Scholar

56. Alemayehu, M, Abreha, K, Yebyo, H et al. (2014) Factors associated with timely initiation and exclusive breast feeding among mothers of Axum town, Northern Ethiopia. Sci J Public Health 2, 394–401.Google Scholar

57. Berhe, H, Mekonnen, B, Bayray, A et al. (2013) Determinants of breast feeding practices among mothers attending public health facilities, Mekelle, Northern Ethiopia; a cross sectional study. Int J Pharmaceut Sci Res 4, 650.Google Scholar

58. Setegn, T, Gerbaba, M & Belachew, T (2011) Determinants of timely initiation of breastfeeding among mothers in Goba Woreda, South East Ethiopia: a cross sectional study. BMC Public Health 11, 217.Google Scholar

59. Tamiru, D & Tamrat, M (2015) Constraints to the optimal breastfeeding practices of breastfeeding mothers in the rural communities of Arba Minch Zuria Woreda, Ethiopia: a community-based, cross-sectional study. South Afr J Clin Nutr 28, 134–139.Google Scholar

60. Regassa, N (2014) Infant and child feeding practices among farming communities in Southern Ethiopia. Kontakt 16, e215–e222.Google Scholar

61. Ekubay, M, Berhe, A & Yisma, E (2018) Initiation of breastfeeding within one hour of birth among mothers with infants younger than or equal to 6 months of age attending public health institutions in Addis Ababa, Ethiopia. Int Breastfeed J 13, 4.Google Scholar

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

63. Tewabe, T (2016) Timely initiation of breastfeeding and associated factors among mothers in Motta town, East Gojjam zone, Amhara regional state, Ethiopia, 2015: a cross-sectional study. BMC Pregnancy Childbirth 16, 314.Google Scholar

64. Tilahun, G, Degu, G, Azale, , T et al. (2016) Prevalence and associated factors of timely initiation of breastfeeding among mothers at Debre Berhan town, Ethiopia: a cross-sectional study. Int Breastfeed J 11, 27.Google Scholar

65. Liben, ML & Yesuf, EM (2016) Determinants of early initiation of breastfeeding in Amibara district, Northeastern Ethiopia: a community based cross-sectional study. Int Breastfeed J 11, 7.Google Scholar

66. Abera, K (2012) Infant and young child feeding practices among mothers living in Harar, Ethiopia. Harar Bull Health Sci 4, 66–78.Google Scholar

67. Getahun, EA, Hayelom, DH & Kassie, GG (2017) Exclusive breast feeding practice and associated factors in Kemba Woreda, Southern Ethiopia, a community based cross-sectional study. Int J Sci Technol Soc 5, 55.Google Scholar

68. Gizaw, Z, Woldu, W & Bitew, BD (2017) Exclusive breastfeeding status of children aged between 6 and 24 months in the nomadic population of Hadaleala district, Afar Region, northeast Ethiopia. Int Breastfeed J 12, 38.Google Scholar

69. Hunegnaw, MT, Gezie, LD & Teferra, AS (2017) Exclusive breastfeeding and associated factors among mothers in Gozamin district, northwest Ethiopia: a community based cross-sectional study. Int Breastfeed J 12, 30.Google Scholar

70. Lenja, A, Demissie, T, Yohannes, , B et al. (2016) Determinants of exclusive breastfeeding practice to infants aged less than six months in Offa district, Southern Ethiopia: a cross-sectional study. Int Breastfeed J 11, 32.Google Scholar

71. Setegn, T, Belachew, T, Gerbaba, M et al. (2012) Factors associated with exclusive breastfeeding practices among mothers in Goba district, south east Ethiopia: a cross-sectional study. Int Breastfeed J 7, 17.Google Scholar

72. Sonko, A & Worku, A (2015) Prevalence and predictors of exclusive breastfeeding for the first six months of life among women in Halaba special woreda, Southern Nations, Nationalities and Peoples’ Region/SNNPR/, Ethiopia: a community based cross-sectional study. Arch Public Health 73, 53.Google Scholar

73. Asfaw, MM, Argaw, MD & Kefene, ZK (2015) Factors associated with exclusive breastfeeding practices in Debre Berhan District, Central Ethiopia: a cross sectional community based study. Int Breastfeed J 10, 23.Google Scholar

74. Teka, B, Assefa, H & Haileslassie, K (2015) Prevalence and determinant factors of exclusive breastfeeding practices among mothers in Enderta woreda, Tigray, North Ethiopia: a cross-sectional study. Int Breastfeed J 10, 2.Google Scholar

75. Sefene, A, Birhanu, D, Awoke, W et al. (2013) Determinants of exclusive breastfeeding practice among mothers of children age less than 6 month in Bahir Dar city administration, Northwest Ethiopia; a community based cross-sectional survey. Sci J Clin Med 2, 153–159.Google Scholar

76. Alemayehu, T, Haidar, J & Habte, D (2009) Determinants of exclusive breastfeeding practices in Ethiopia. Ethiop J Health Dev 23, issue 1; available at https://www.ajol.info/index.php/ejhd/article/view/44832 Google Scholar

77. Asemahagn, MA (2016) Determinants of exclusive breastfeeding practices among mothers in Azezo district, northwest Ethiopia. Int Breastfeed J 11, 22.Google Scholar

78. Liben, ML, Gemechu, YB, Adugnew, M et al. (2016) Factors associated with exclusive breastfeeding practices among mothers in Dubti town, Afar regional state, northeast Ethiopia: a community based cross-sectional study. Int Breastfeed J 11, 4.Google Scholar

79. Seid, AM, Yesuf, ME & Koye, DN (2013) Prevalence of exclusive breastfeeding practices and associated factors among mothers in Bahir Dar city, Northwest Ethiopia: a community based cross-sectional study. Int Breastfeed J 8, 14.Google Scholar

80. Tadesse, T, Mesfin, F & Chane, T (2016) Prevalence and associated factors of non-exclusive breastfeeding of infants during the first six months in rural area of Sorro District, Southern Ethiopia: a cross-sectional study. Int Breastfeed J 11, 25.Google Scholar

81. Tewabe, T, Mandesh, A, Gualu, T et al. (2017) Exclusive breastfeeding practice and associated factors among mothers in Motta town, East Gojjam zone, Amhara Regional State, Ethiopia, 2015: a cross-sectional study. Int Breastfeed J 12, 12.Google Scholar

82. Arage, G & Gedamu, H (2016) Exclusive breastfeeding practice and its associated factors among mothers of infants less than six months of age in Debre Tabor town, Northwest Ethiopia: a cross-sectional study. Adv Public Health 2016, 3426249.Google Scholar

83. Elyas, L, Mekasha, A, Admasie, A et al. (2017) Exclusive breastfeeding practice and associated factors among mothers attending private pediatric and child clinics, Addis Ababa, Ethiopia: a cross-sectional study. Int J Pediatr 2017, 8546192.Google Scholar

84. Egata, G, Berhane, Y & Worku, A (2013) Predictors of non-exclusive breastfeeding at 6 months among rural mothers in east Ethiopia: a community-based analytical cross-sectional study. Int Breastfeed J 8, 8.Google Scholar

85. Mekuria, G & Edris, M (2015) Exclusive breastfeeding and associated factors among mothers in Debre Markos, Northwest Ethiopia: a cross-sectional study. Int Breastfeed J 10, 1.Google Scholar

86. Tamiru, D, Belachew, T, Loha, E et al. (2012) Sub-optimal breastfeeding of infants during the first six months and associated factors in rural communities of Jimma Arjo Woreda, Southwest Ethiopia. BMC Public Health 12, 363.Google Scholar

87. Echamo, M (2012) Exclusive breast feeding in Arbaminch, SNNPR, Ethiopia. Harar Bull Health Sci 5, 44–59.Google Scholar

88. Dorgham, L, Hafez, S, Kamhawy, H et al. (2014) Assessment of initiation of breastfeeding, prevalence of exclusive breast feeding and their predictors in Taif, KSA. Life Sci J 11, 1.Google Scholar

89. Agho, KE, Dibley, MJ, Odiase, JI et al. (2011) Determinants of exclusive breastfeeding in Nigeria. BMC Pregnancy Childbirth 11, 2.Google Scholar

90. Kanhadilok, S & McGrath, JM (2015) An integrative review of factors influencing breastfeeding in adolescent mothers. J Perinat Educ 24, 119.Google Scholar

91. Emmanuel, A (2015) A literature review of the factors that influence breastfeeding: An application of the health belief model. Int J Nurs Health Sci 2, issue 3, 28–36.Google Scholar

92. Balogun, OO, Dagvadorj, A, Anigo, KM et al. (2015) Factors influencing breastfeeding exclusivity during the first 6 months of life in developing countries: a quantitative and qualitative systematic review. Matern Child Nutr 11, 433–451.Google Scholar

93. Kavle, JA, LaCroix, E, Dau, H et al. (2017) Addressing barriers to exclusive breast-feeding in low- and middle-income countries: a systematic review and programmatic implications. Public Health Nutr 20, 3120–3134.Google Scholar

94. Pereira-Santos, M, Santana, MdS, Oliveira, DS et al. (2017) Prevalence and associated factors for early interruption of exclusive breastfeeding: meta-analysis on Brazilian epidemiological studies. Rev Bras Saude Matern Infant 17, 59–67.Google Scholar

95. Ogbo, FA, Eastwood, J, Page, A et al. (2017) The impact of sociodemographic and health-service factors on breast-feeding in sub-Saharan African countries with high diarrhoea mortality. Public Health Nutr 20, 3109–3119.Google Scholar

96. Chandrashekhar, T, Joshi, H, Binu, V et al. (2007) Breast-feeding initiation and determinants of exclusive breast-feeding – a questionnaire survey in an urban population of western Nepal. Public Health Nutr 10, 192–197.Google Scholar

97. Barennes, H, Empis, G, Quang, TD et al. (2012) Breast-milk substitutes: a new old-threat for breastfeeding policy in developing countries. A case study in a traditionally high breastfeeding country. PLoS One 7, e30634.Google Scholar

98. Radwan, H (2013) Patterns and determinants of breastfeeding and complementary feeding practices of Emirati mothers in the United Arab Emirates. BMC Public Health 13, 171.Google Scholar

99. Ghwass, MMA & Ahmed, D (2011) Prevalence and predictors of 6-month exclusive breastfeeding in a rural area in Egypt. Breastfeed Med 6, 191–196.Google Scholar

100. Yılmaz, E, Öcal, FD, Yılmaz, ZV et al. (2017) Early initiation and exclusive breastfeeding: factors influencing the attitudes of mothers who gave birth in a baby-friendly hospital. Turk J Obstet Gynecol 14, 1–9.Google Scholar

101. El-Gilany, AH, El-Wehady, A & El-Hawary, A (2008) Maternal employment and maternity care in Al-Hassa, Saudi Arabia. Eur J Contracept Reprod Health Care 13, 304–312.Google Scholar

102. Ogunlesi, TA (2010) Maternal socio-demographic factors influencing the initiation and exclusivity of breastfeeding in a Nigerian semi-urban setting. Matern Child Health J 14, 459–465.Google Scholar

103. Pandey, S, Tiwari, K, Senarath, U et al. (2010) Determinants of infant and young child feeding practices in Nepal: secondary data analysis of Demographic and Health Survey 2006. Food Nutr Bull 31, 334–351.Google Scholar

104. Perera, PJ, Ranathunga, N, Fernando, MP et al. (2012) Actual exclusive breastfeeding rates and determinants among a cohort of children living in Gampaha district Sri Lanka: a prospective observational study. Int Breastfeed J 7, 21.Google Scholar

Table 1 Characteristics of studies included in the present systematic review and meta-analysis on factors affecting timely initiation of breast-feeding (TIBF) in Ethiopia

Table 2 Characteristics of studies included in the present systematic review and meta-analysis on factors affecting exclusive breast-feeding (EBF) in Ethiopia