Prevalence and Factors Associated with Early Initiation of Breastfeeding (EIBF) in Rural Areas of Burkina Faso ()
1. Introduction
Breastfeeding remains the best nutritional choice for newborns, especially in developing countries where HIV-prevalence rates are low [1]. Moreover, several studies suggest that early initiation of breastfeeding (EIBF) defined by the WHO as putting a newborn to breast within one hour of birth [2], has multiple health benefits for the newborns, infants and their mothers [3] [4]. A systematic review showed that newborns with late initiation of breastfeeding had a 33% higher risk of neonatal death as compared to those with EIBF [5]. The same study showed that EIBF was also associated with a reduced risk of maternal postpartum hemorrhages [6]. For all the above mentioned reasons, WHO strongly recommends that all newborns are set to breast within one hour of birth.
However, global data showed that only 3 out of 5 newborns worldwide received EIBF in 2018, most of them from developing countries [7]. Thus, the need to better identify factors increasing EIBF [8]-[10] and those described as being its potential barriers [11]-[13].
In Burkina Faso, a national nutritional survey among children younger than two years reported a 40% EIBF-rate in 2020 [14]. However, there are regional variations, and the few prospective studies reports are inconsistent with that of the MoH [15]. We took advantage of the Alive and Thrive interventions evaluation datasets to estimate the prevalence and to identify factors associated with EIBF in rural Burkina Faso.
2. Methods
2.1. Study Area and Context of the Original Study
The study was carried out in Boucle du Mouhoun region, West of Burkina Faso in the Provinces of Mouhoun and Bale (Figure 1). The capital city from the region is Dedougou town, located 232 km from Ouagadougou, the Burkina Faso’s capital city. The area belongs to that labelled as the main granary of the country with annual rainfalls of 800 - 1200 mm. Farming and animal husbandry are the main sources of income for a mainly rural population. Small trading is also another activity in small towns of the area. From health perspective, the area had a under-five mortality rates of 51‰, and IMR of 30‰ and a NMR of 29‰ from the last DHS in 2021 [16]. Malnutrition is common among under-five children at a global prevalence of 52% with 23% being stunted and 11% wasted [14]. Malaria, acute respiratory infections and diarrhea are reported to be the main causes of child deaths [16] [17]. The health system is made of one regional referral hospital, 15 district hospitals and 284 primary health facilities [17]. Over 70% of mothers have no formal education [16] and the free policy for pregnant mothers and children under five was not yet formally in place at the time of the original study. However, the Alive and Thrive intervention project was partly in place in the intervention villages of the study area. The intervention in Burkina Faso is described elsewhere [18] and consisted of the promotion of infants and children good nutritional practices at community-and-facility levels. In summary, staff from primary health facilities received a one week training on EIBF, exclusive breastfeeding, complementary feeding and its promotion in all intervention-arm facilities. Community-health workers (CHWs) from the same facilities received a training to promote the children good nutritional practices at community-level in villages covered by each facility. This was done through household visits, using an adapted material and in local dialects from the areas [18]. Pregnant or lactating women were booked to receive individual interpersonal communication sessions at the local facility or during home visits by local CHWs. Moreover, community-mobilization was another intervention activity aimed to reach larger groups such as husbands, mothers-in-law and other women of childbearing age. Villages from the control arm received no Alive & Thrive intervention and kept ongoing routine practices for both health staff and CHWs.
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Figure 1. Map of the Boucle du Mouhoun region, West of Burkina Faso. (Source: https://www.researchgate.net/figure/Showing-the-Boucle-de-Mouhoun-Region-and-its-6-Administrative-Provinces_fig1_333201681).
2.2. Type of Study
We conducted a secondary analysis of the data from an originally cross-sectional study, that was carried out between June and September 2016 in twelve villages from Boucle du Mouhoun region. This original study aims at assessing the consistency of mothers practices and reports on exclusive breastfeeding in the framework of a validation study as part of the evaluation of the Alive and Thrive interventions [18].
2.3. Data Sources and Sampling of Study Participants
The Data were extracted from that of a questionnaire completed as part of the validation study. We included in our analyses data from all eligible mother-infant pairs from the original study.
In the original database, mother-child pairs were randomly selected from 12 villages in two provinces (Mouhoun and Balé, Figure 1). Six of the villages were located within the intervention area while the other half belonged to the area where no Alive and Thrive intervention was implemented. In each village, records from the local health facility maternity register, were used to randomly sample 13 mother-child pairs whom infants were younger than six months on the day of enrolment. The total sample size required for the original validation study was 156 mother-infant pairs.
2.4. Study Population
Mother-infant pairs from selected study villages with a child younger than 6 months on the day of enrolment were targeted. Moreover, the following inclusion criteria were used:
Mother delivered at the local health facility or were recorded in the maternity register.
Mother-infant pair is alive and is in apparent good health.
Mother-infant pair lives in one of the study villages.
Mother has given written informed consent to participate in the original study.
Mothers with multiple live births and mother-infant records not being sampled to be part of the study were excluded.
2.5. Variables Description and Original Study Data Collection
The original study questionnaire was structured into four sections, namely sociodemographic backgrounds, clinical assessments, nutritional evaluation and the laboratory component of the validation study. Our extraction sheet contained variables from the first three sections for each mother-infant pair, that of the husband and for the household. Thus, variables on mother’s age, parity, educational level, occupation, sources of income and household’s assets were extracted as were data of the baby’s age, sex and birth weight. Of the nutritional variables of interest, we included data on mother-child weight and height at inclusion and that of the 23 foods items on feeding the baby since birth such as prelacteals, colostrum, breastmilk, liquids, solid foods and medicines.
The variable on EIBF was labeled as “how many time soon after birth did you for the first time set your child to breast?”; the optional responses were on the following order: 1) exact time elapsed in min if less than an hour, 2) 1 - 12 hours, 3) 12 - 24 hours, 4) 24 - 72 hours, 5) >72 hours, 6) other response, specify. The EIBF variable was then recoded into two categories, i.e., “yes” if the baby was put to breast within one hour of birth; and “no”, otherwise. Data collectors as per the questionnaire SOPs were instructed to try their best to prioritize the time to initiate breastfeeding in min or hours. For this purpose, they received training on how to assist the mothers to best remember and estimate the time to set their babies to breast the first time. The survey techniques included questioning the mother on the time of birth (morning, midday, afternoon, evening), the context of delivery and then how soon she thinks her baby was put to breast. Maternal age was recorded in completed years and baby’s age calculated from her/his date of birth. Because this study was observational, the data surveyors were blinded about the Alive and Thrive intervention clusters. The original data were double entered in Epidata Entry software (https://www.epidata.dk/), cleaned during the field work that also received regular field supervisions from experienced study investigators. We therefore used a cleaned dataset that was archived in Centre MURAZ server by the study investigators, to run current analyses.
2.6. Statistical Analyses
All data analyses were conducted with Stata SE 16.0 (https://www.stata.com/).
We first performed a descriptive analysis to generate means (±SD) and median (IQR) for continuous variables; and proportions (with 95% CIs) and frequency tables for relevant categorical variables. Household socioeconomic index was built from tertiles using a principal component analysis (PCA) that included household’s assets, household sources of water and energy, and housing items in the model. We also calculated maternal BMI and child’s z-scores using the WHO-2006 reference growth chart. Maternal BMI was used to categorize mothers into underweight (<18%), normal weight (18% - 25%) and overweight (>25%). The z-scores were thereafter used to classify the child nutritional status into stunting (HAZ < −2SD), wasting (WHZ < −2SD) and underweight (WAZ < −2SD) accounting for sex and age.
All descriptive estimates accounted for the clustering of participants using the svy command in Stata.
To identify the factors associated with EIBF, we first used an univariable logistic regressions method to obtain unadjusted Odds Ratios (ORs) with robust variance estimations.
As to build the multivariable analysis model, a threshold of <20% was set for variables in crude analysis to be included. The final model was obtained using a forward stepwise multivariable logistic regressions method. Fitness of the final model was assessed using the maximum likelihood ratios method. Variables with adjusted ORs significant at p < 5% were considered as associated to EIBF.
2.7. Ethical Considerations
The original validation study was approved by the Institutional review board from Centre MURAZ (No2015/017) and administrative clearance was received from the MoH through the regional health directorate of Boucle du Mouhoun. All mothers gave an individual informed and written consent prior inclusion in the study.
3. Results
Socio-Demographic and Clinical Characteristics of the Participants
A total of 157 mother-infant pairs were included in our analyses. The median maternal age was 27 years (IQR: 21 - 33), with 66.9% aged 20 - 35 years. Almost all the women were married (96.2%) and 31.2% were in polygamous households. Ten percent of the mothers had secondary education level. Nineteen percent of the mothers were housewives or had no income-generating activities (Table 1).
Table 1. Socio-demographic baseline of mothers, fathers, households and infants and prevalence of early initiation of breastfeeding (EIBF) per those variables among 157 participants from a secondary analysis of a breastfeeding cross-sectional study in Boucle du Mouhourn region, West of Burkina Faso.
Variables n = 157 |
N (%) |
Prevalence of EIBFa N (%) |
Mother Baseline |
Intervention area |
|
|
Intervention clusters |
79 (50.3) |
15 (18.9) |
Control clusters |
78 (49.7) |
05 (06.4) |
Maternal age (years) |
|
|
<20 |
20 (12.7) |
01 (05.0) |
20 - 35 |
105 (66.9) |
16 (15.2) |
>35 |
32 (20.4) |
03 (09.4) |
Maternal marital status |
|
|
Married/cohabiting |
151 (96.2) |
17 (11.3) |
Single/Others |
06 (03.8) |
03 (50.0) |
Mother lives in a polygamous household |
|
|
Yes |
49 (31.2) |
06 (12.2) |
No |
108 (68.8) |
14 (12.9) |
Maternal education level |
|
|
None |
96 (61.2) |
08 (09.4) |
Primary school |
45 (28.7) |
06 (13.3) |
Secondary school |
16 (10.1) |
05 (31.3) |
Maternal occupation |
|
None/housewife |
30 (19.1) |
03 (10.0) |
Farming |
49 (31.2) |
06 (12.2) |
Trading/Others |
78 (49.7) |
11 (14.1) |
Maternal parity |
|
|
1 - 2 |
57 (36.3) |
04 (07.0) |
3 - 6 |
82 (52.2) |
15 (18.3) |
≥7 |
18 (11.5) |
01 (5.6) |
Maternal Body Mass index (BMI)b |
|
Underweight (<18%) |
10 (6.4) |
01 (10.0) |
Normal (18% - 25%) |
125 (79.6) |
17 (13.6) |
Overweight (>25%) |
22 (14.0) |
02 (09.1) |
Father baseline |
Father age (years) |
|
<35 |
82 (52.2) |
11 (13.4) |
≥35 |
75 (47.8) |
09 (12.0) |
Father education level |
|
None |
105 (66.9) |
13 (12.4) |
Primary school |
37 (23.6) |
05 (13.5) |
Secondary school |
15 (09.6) |
02 (13.3) |
Household socioeconomic indexc |
|
|
Low |
55 (35.0) |
11 (20.0) |
Average |
50 (31.9) |
05 (10.0) |
Least poor |
52 (33.1) |
04 (07.7) |
Child baseline |
Child’s age at enrolment (months) |
|
1 - 3 |
101 (63.3) |
15 (14.9) |
3 - 5 |
56 (35.7) |
05 (08.9) |
Child sex |
|
|
Female |
81 (51.6) |
13 (16.1) |
Male |
76 (48.4) |
07 (09.2) |
The newborn was premature at birth |
|
No |
156 (99.4) |
20 (12.8) |
Yes |
01 ( 0.6) |
0 ( 0.0) |
Place of birth |
|
Health facility |
154 (98.0) |
20 (12.9) |
Home |
03 (02.0) |
0 ( 0.0) |
Child’s birth weight (g)d |
|
<2500 |
13 (08.4) |
0 (0.0) |
≥2500 |
141 (91.6) |
20 (14.2) |
Child nutritional status at enrolmente |
|
|
Stunted (HAZ < −2SD) |
08 (05.1) |
01 (12.5) |
Wasted (WHZ < −2SD) |
22 (14.0) |
04 (18.2) |
Underweight (WAZ < −2SD) |
11 (07.0) |
03 (27.3) |
aEIBF: Early initiation of breastfeeding; bBMI: Calculated as weight (in Kg)/height^2(in(m2); cHousehold socioeconomic index was generated from household’s assets (car, motorbike, bicycle, phone, TV, radio, refrigerator, chart, etc.), household source of water (river, well, borehole, tap water, etc.), household source of energy (battery, solar pane, electricity, none, etc.) and the housing items (walls, floor, roof); an overall index built from PCA was thereafter converted into tertiles (low, average, least poor); dThree children born at home but sent few hours later to the facility did not have birth weight recorded; eCategories were based on WHO-reference growth study (2006) and z-scores adjusted for the child age and sex.
More than ¾ of them were multiparae, and 52.2% had already given birth 3 to 6 times. Mothers had delivered in a local health facility in 98% of births. Maternal BMIs were normal for 79.6%. The median age for the husband was 34 years (IQR: 29 - 41), 66.9% had no formal education (Table 1). The mean infant age was 2.6 months (±1.2) and 51.6% were girls. Almost all (99.4%) were born at full term gestation based on mothers’ reports with a median birth weight of 3000 g and low birth weight for 8.4%.
Prevalence of EIBF
Overall, 20 out of 157 infants in our study benefited from EIBF, i.e. 12.7%, with a 95% CI of [6.8% - 22.5%].
Analysis of factors associated with EIBF
Univariable logistic regressions found that 6 variables were associated with EIBF with a p value < 0.2 (Table 2).
Table 2. Univariable and multivariable logistic regressions of variables associated with increased prevalence-rates of early initiation of breastfeeding (EIBF) among 157 mother-infants pairs in the Boucle du Mouhoun region, West of Burkina Faso.
Variables |
N (%) with EIBFa |
Univariable analysis ORcrude [95% CIb] |
P |
Multivariable analysis ORadjusted [95% CI] |
p |
Mother Baseline |
Intervention area |
|
|
|
|
|
Intervention clusters |
15 (18.9) |
3.42 [0.92 - 12.59] |
0.065 |
5.5 [1.56 - 19.47] |
0.008 |
Control clusters |
05 (06.4) |
1.00 |
|
|
Maternal age (years) |
|
|
|
|
|
<20 |
01 (05.0) |
1.00 |
0.289 |
|
|
20 - 35 |
16 (15.2) |
3.66 [0.69 - 19.45] |
|
|
>35 |
03 (09.4) |
2.00 [0.35 - 11.43] |
|
|
|
Maternal marital status |
|
|
|
|
|
Married/cohabiting |
17 (11.3) |
1.00 |
0.046 |
|
|
Single/Others |
03 (50.0) |
7.57 [1.03 - 55.38] |
5.5 [0.46 - 65.67] |
0.178 |
Mother lives in a polygamous household |
|
|
|
|
Yes |
06 (12.2) |
1.00 |
0.945 |
|
|
No |
14 (12.9) |
1.03 [0.36 - 2.90] |
|
|
Maternal education level |
|
|
|
|
|
None |
09 (09.4) |
1.00 |
0.0004 |
|
|
Primary school |
06 (13.3) |
1.41 [0.34 - 5.71] |
2.3 [0.63 - 8.55] |
0.200 |
Secondary school |
05 (31.3) |
4.70 [1.91 - 11.57] |
10.7 [1.64 - 69.94] |
0.013 |
Maternal occupation |
|
|
|
|
|
None/housewife |
03 (10.0) |
1.00 |
0.840 |
|
|
Farming |
06 (12.2) |
1.16 [0.22 - 5.98] |
|
|
Trading/Others |
11 (14.1) |
1.44 [0.37 - 5.54] |
|
|
Maternal parity |
|
|
|
|
|
1 - 2 |
04 (07.0) |
1 |
0.175 |
|
|
3 - 6 |
15 (18.3) |
2.88 [0.94 - 8.84] |
9.5 [1.70 - 53.22] |
0.010 |
≥7 |
01 (5.6) |
0.74 [0.09 - 5.64] |
1.91 [0.13 - 26.79] |
0.628 |
Maternal Body Mass index (BMI) |
|
|
|
|
|
Underweight |
01 (10.0) |
0.78 [0.07 - 8.10] |
0.726 |
|
|
Normal |
17 (13.6) |
1.00 |
|
|
Overweight |
02 (09.1) |
0.60 [0.17 - 2.11] |
|
|
Father baseline |
Father age (years) |
|
|
|
|
|
<35 |
11 (13.4) |
1.00 |
0.759 |
|
|
≥35 |
09 (12.0) |
0.89 [0.42 - 1.87] |
|
Father education level |
|
|
|
|
|
None |
13 (12.4) |
1.00 |
0.948 |
|
|
Primary school |
05 (13.5) |
1.11 [0.44 - 2.77] |
|
|
Secondary school |
02 (13.3) |
1.18 [0.31 - 4.42] |
|
|
Household socioeconomic indexc |
|
|
|
|
|
Low |
11 (20.0) |
1.00 |
0.094 |
|
|
Average |
05 (10.0) |
0.49 [0.16 - 1.53] |
0.4 [0.11 - 1.65] |
0.225 |
Least poor |
04 (07.7) |
0.37 [0.12 - 1.12] |
0.4 [0.10 - 1.92] |
0.285 |
Child baseline |
Child sex |
|
|
|
|
|
Female |
13 (16.1) |
1.00 |
0.175 |
|
|
Male |
07 (09.2) |
0.53 [0.22 - 1.31] |
0.5 [0.15 - 1.72] |
0.280 |
The newborn was premature at birth |
|
|
|
|
|
No |
20 (12.8) |
1.00 |
- |
|
|
Yes |
0 (0.0) |
- |
|
|
Place of birth |
|
|
|
|
|
Health facility |
20 (12.9) |
1.00 |
- |
|
|
Home |
0 (0.0) |
- |
|
|
Child birth weight (g)d |
|
|
|
|
|
<2500 |
0 (0.0) |
- |
- |
|
|
≥2500 |
20 (14.2) |
1.00 |
|
|
aEIBF: Early initiation of breastfeeding, OR: odds ratio, bCI = confidence intervals; cHousehold socioeconomic index was generated from household’s assets (car, motorbike, bicycle, phone, TV, radio, refrigerator, chart, etc.), household source of water (river, well, borehole, tap water, etc.), household source of energy (battery, solar pane, electricity, none, etc.) and the housing items (walls, floor, roof); an overall index built from PCA was thereafter converted into tertiles (low, average, least poor); dThree children born at home but sent few hours later to the facility did not have birth weight recorded.
These were the study intervention areas, maternal marital status, maternal education, maternal parity, the household socio-economic index and the child’s sex (Table 2). Multivariable analyses adjusting for all above mentioned variables showed that three variables were significantly (p < 0.05) associated with EIBF. Women from the intervention villages had 5.5 times higher chance to initiate early breastfeeding compared to their peers from control villages (OR = 5.5, 95% CI: 1.56 - 19.47, p = 0.008, Table 2). Similarly, mothers with secondary education had 10.7 times higher likelihood for EIBF (OR = 10.7; 95% CI: 1.6 - 69.9) as to those with no formal education. Finally, women who had given birth 3 to 6 times before were at 9.5 higher odds of EIBF compared to pauciparae mothers (OR = 9.5, p = 0.010, Table 2).
4. Discussion
Our study found that the prevalence of EIBF in this rural area of Burkina Faso was 12.7%, much lower than the WHO-recommendations [19]. The observed low prevalence in this study is inconsistent with findings from other African studies where health facility delivery was high [9] [20]-[24]. The prevalence of EIBF in this study is also much lower than national (47% and 63%) and regional (37% and 73%) averages reported in previous national nutritional surveys from Burkina Faso, respectively in 2015 and 2020 [14] [25]. Nevertheless, our prevalence of EIBF was similar to that reported by a prospective large cross-sectional study in the same region and almost at the period, that was of 9.4% in a group of mothers whose infants were 0 - 11 months older [15]. Another national nutrition survey from 2014 reported a 11.7% prevalence of EIBF in the Southwest region of Burkina Faso [26].
We believe that our estimation of the prevalence of EIBF is explained by several reasons amongst which a difference of study population as compared to other reports and possibly, further implementation of breastfeeding interventions in the area since 2017. Indeed, national nutritional surveys commonly rely on a population of mother-child pairs where children are aged 0 - 23 months. This encompasses a strong recall bias especially if the proportion of children older than one year is high, i.e., a longer recall period for the mother. Another reason of such low prevalence as compared to nation-wide and regional data from Burkina Faso may link to the type and training of data collectors. Our team has specialized in breastfeeding studies [27] and therefore, it is likely the vocabulary is more precise and the questionnaire helps mothers best remember the time to initiation of breastfeeding. Finally, it is known that cultural practices in rural settings of Burkina Faso are not always favorable to EIBF especially where the promotion of good young infant feeding practices is low [28].
Our results are consistent with that of previous studies that showed the importance of maternal education and that of the promotion of exclusive breastfeeding in increasing prevalence-rates of EIBF both in Burkina Faso and other African settings [7]-[9] [15]. High school maternal education may be especially relevant in a context of very low literacy as it increases general knowledge and possibly, maternal self-health education. Two major trials conducted in rural Burkina Faso showed increasing reported rates of EIBF [18] [27]. However, it is important to remember that our data were observational and our sample size relatively small.
The association of parity with increased prevalence of EIBF is inconsistent across literature; we were expecting paucipare mothers to be the ones with higher rates of EIBF but our findings suggest the opposite. One explanation would be that mothers are improving their knowledge and practices of the young infant good nutritional practices over deliveries as they are repeatedly exposed to the good messages and to the health system. Other possible explanations may include the challenges faced by first-time mothers, such as higher anxiety or less practical experience, which could contribute to their lower breastfeeding rates at birth.
Despite its relevant findings outlined above, our study included several limitations among which, we can mention, potential memory bias associated with the use of self-reported data, the inability to establish causality based on a cross-sectional design, and the limited generalisability of the results obtained from a small, localised sample.
5. Conclusion
The prevalence of EIBF in this rural area of Burkina Faso was low. High school maternal education, multiparity and the intervention areas appeared to be the three factors associated with an increased prevalence of EIBF. Our data are consistent with previous reports and highlight the need for increased girls schooling and a scaling-up of young infant good nutritional practices interventions such as integrating EIBF counseling into routine antenatal visits or leveraging community health workers as The Alive & Thrive intervention in rural Burkina Faso.
Authors’ Contribution
AH Diallo: Writing original draft, Conceptualization, Investigation, Data analysis. S Ouattara: Review, Editing. JV Gare: Review, Editing. S.B Saguirou: Review, Editing. J Diendéré: Review, Editing. B Gnoumou: Data curation. RM Bamouni: Review, Editing, Investigation. S. Ouédraogo: Review, Editing, Investigation.
All authors reviewed and approved the final manuscript.
Funding
This work was supported by the Alive &Thrive Project [grant OPP50838/2014] and the Ministry of Health, Burkina Faso [Data collection, Health facilities].