ABSTRACT
Background and Aims
The most effective intervention to reduce child morbidity and mortality both in developed and developing countries is the promotion of optimal breastfeeding practices. Breastfeeding practices are usually affected by influential people in the family, such as the husband. Therefore, this study aimed to evaluate the effect of a couple‐based optimal breastfeeding promotion and support intervention on the frequency of child morbidity in central Ethiopia.
Methods
A two‐arm, parallel, cluster randomized controlled trial was carried out among couples in a community setting in the Hadiya Zone, Central Ethiopia. A total of 408 couples from 16 clusters were randomly assigned to either the intervention group (n = 204) or the control group (n = 204). Fathers and mothers in the intervention arm received breastfeeding education and support interventions, while those in the control arm received existing routine care. The outcome variable was measured by assessing three specific morbidities in children: diarrhoea, fever, and acute respiratory illnesses during the post‐delivery period as count data. A zero‐inflated multivariable negative binomial regression (ZINB) model was used for the analysis of data. The incidence rate ratio (IRR) with a 95% CI was used to report the result.
Results
In the 6‐month follow‐up, 34.5% of infants remained healthy with no episodes of illness. In this trial, the incidence of morbidity was decreased by 92.7% (IRR = 0.073, 95% CI: 0.039–0.138, p < 0.001) for neonatal and infants whose parents received optimal breastfeeding promotion and support interventions compared to infants whose mothers received routine care during the intervention period.
Conclusion
Couple‐based optimal breastfeeding promotion intervention has shown a protective effect against the frequency of neonatal and infants morbidity, highlighting the effectiveness in community settings of this optimal breastfeeding counselling model that includes the father.
Trial Registration
This trial was registered on ClinicalTrials. gov with identifier (NCT number): NCT05173454, First registered on 30/12/2021.
Keywords: child morbidity, couples, education interventions, Ethiopia, optimal breastfeeding
1. Introduction
Breastfeeding is one of the foundations of child health, development, and survival. It is especially important where diarrhoea, pneumonia, and undernutrition are common causes of mortality in children under 5 years of age [1]. Exclusive breastfeeding, preceded by timely initiation and appropriate complementary feeding practices, is universally accepted as an essential element for the satisfactory growth and development of infants and for the prevention of childhood illness [2].
Infection and improper child‐feeding practices account for 60% of infant and child deaths worldwide, with suboptimal BF practices being the reason for two‐thirds of these cases [2]. Mainly, late initiation and nonexclusive breastfeeding are significant causes of diarrhoea during the infant and young child age [3]. It is estimated that suboptimal breastfeeding, especially non‐exclusive breastfeeding in the first 6 months of life, results in 1.4 million deaths and 10% of the disease burden in children younger than 5 years [4], and diarrhoeal diseases and acute respiratory infections (ARIs) are the leading causes of morbidity and mortality in children under 5 years old [5]. Optimal breastfeeding may potentially save the lives of about 800,000 children in low‐income settings annually [5].
Promotion of breastfeeding can reduce diarrhoea morbidity rates by 8%–20% and diarrhoea mortality rates by 24%–27% in the first 6 months of life. For children ages 0–59 months, diarrhoea morbidity rates would be reduced by 1%–4% and mortality rates by 8%–9% by promotion of breastfeeding [6]. In 2016, almost 653,000 deaths were attributed to lower ARIs in children below 5 years old [7]. Furthermore, ARI is responsible for almost 20% of all deaths in children [7, 8].
Contrary to the World Health Organization recommendation on optimal breastfeeding practices, in Ethiopia, 59% of infants under 6 months are exclusively breastfed. Nine percent of infants under 6 months use a bottle with a nipple, a practice that is discouraged because of the risk of exposing the child to illness [9]. The rate of pre‐lacteal feeding among children in Ethiopia is 26.95% [10], while the practice of initiating breastfeeding late is also similar at 26.4% [11]. All of these practices are considered sub‐optimal for breastfeeding and can put the child at risk of illness.
The husband is the main decision‐maker in the family, especially in most of Ethiopian society. Men's involvement in maternal and child health care services is one of the recognized strategies to improve the utilization of maternal and child health services [12]. The available evidence on the effect of male‐partner‐targeted interventions aimed at increasing exposure to breastfeeding practices found that mother‐father pairs who received interventions were more likely to practice breastfeeding than those who did not receive interventions [13, 14, 15, 16, 17, 18, 19]. However, these studies did not consider the impact on infant health outcomes such as child morbidity. To the best of the investigator's knowledge, there is a scarcity of evidence that evaluates the effects of couple‐based optimal breastfeeding promotion and support intervention on child morbidity for children under 6 months of age in resource‐limited settings like Ethiopia. Therefore, this study aimed to evaluate the effect of a couple‐based optimal breastfeeding promotion and support intervention on the frequency of child morbidity in central Ethiopia.
2. Methods
2.1. Study Setting
The investigation took place in the Hadiya Zone of central Ethiopia, recognized as one of the seven administrative zones and three special woredas within the region. The Hadiya Zone is divided into four town administrations and thirteen districts. The Central Statistics Agency's (CSA) 2007 Census estimate of the population of the zone is 1,727,920 (846,681 men and 881,239 women). Covering 3593.31 square kilometres, the Hadiya Zone has a population density of 342.64 persons per square kilometre. The trial was held in the Hadiya zone of central Ethiopia, namely in the districts of Gibe and Soro. There are 333,117 people living in the two districts of Soro and Gibe combined; 11,526 of them are estimated to be pregnant. The two districts (Soro and Gibe) have a total of 55 Kebeles (the lowest administrative unit). There are 65 healthcare facilities spread over the two districts. These consist of two primary hospitals, one in the Soro area and one in the Gibe district; 55 health posts; and 8 health centres.
2.2. Design and Participants
The design and methods used in this trial are described in detail in a previously published paper [20]. The intervention trial used a two‐arm, parallel, single‐blind, cluster‐randomized controlled trial design with a 1:1 allocation ratio. The study involved a cluster randomized pre‐test and a post‐test trial design. The trial was conducted and reported in accordance with the CONSORT recommendations for cluster‐randomized trials [21]. The districts of Soro and Gibe were the sites of the intervention. Kebeles (clusters) were used as the trial's randomization units in both districts, and they were randomized to either the intervention or control groups. The duration of the intervention was 9 months. Couples recruited during the third trimester of pregnancy and followed up until 6 months postpartum comprised the study participants. Couples who shared a residence or were in regular contact were eligible. Mothers with severe medical conditions and those with multiple pregnancies were excluded, as were couples who separated, divorced, or moved beyond the research region during the baseline data collection.
2.2.1. Sample Size Determination
G‐Power statistical software was utilized to estimate the sample size. The sample size was calculated using a two‐population proportion formula considering an estimated prevalence (P1) of mothers utilizing the optimal breastfeeding practices at 6 months of 45% [22]. It is also assumed that following the intervention, there will be a 20% improvement in optimum breastfeeding practices, with an estimated rate of 65% (P2), a 95% confidence interval, a one‐tailed test, an α error of 0.05, 80% power, and an allocation ratio of 1:1. This gave a total sample size of 170 (n = 85 per group). To account for cluster design, DE = 1 + ICC (m‐1) [23], where m = 26 average number of participants in a cluster, ICC = 0.05 [24], DE = 2. Therefore, it was multiplied by a design effect of 2. By adding a 20% loss of follow‐up, the final sample size was 408 (204 in intervention and 204 in control groups).
2.2.2. Sampling Procedures
Two districts, Gibe and Soro, were purposively selected from the 13 districts in the Hadiya Zone. These two districts comprise a total of 54 Kebeles. Sixteen geographically non‐adjacent clusters were identified from the existing Kebeles in the two study districts. Prior to the Kebeles being randomized into the intervention or control group, the health extension worker's logbook was used to identify the eligible male partners and their pregnant wives from the selected Kebeles. However, recruitment began after clusters were randomized. From each cluster, the same number of participants were chosen. For the study, all non‐adjacent Kebeles were considered; however, only those that are far enough apart and have at least one kebele between clusters that might serve as a buffer space between them were selected.
2.3. Randomization
Kebeles were assigned to either the intervention or control clusters using a simple randomization technique. From the study districts (Soro and Gibe), 16 clusters (kebeles) that are non‐adjacent to each other were identified purposely. The 16 clusters were ordered alphabetically. Then, in the Excel sheet, random numbers were generated and put in ascending order. Then the first 8 clusters were assigned to the intervention group, and the remaining 8 were assigned to a control group. All randomization procedures were done by a blinded biostatistician.
2.3.1. The Intervention
The intervention was carried out during the antenatal and postnatal periods, from October 2022 to the end of June 2023, for 9 months. The intervention was designed based on social cognitive theory [25]. Eight health care workers from the nearest health centre to the intervention cluster (Kebeles) were selected as counsellors and trained for 3 days by the researcher to provide the intervention. The intervention consisted of three components that included group education, provision of printed leaflets and home visits. The intervention components and activities are summarized with compliance results in Table 1.
Table 1.
Intervention components and activities implemented in intervention sites in Hadiya Zone, central Ethiopia.
| No. | Intervention components and activities | Compliance results |
|---|---|---|
| 1 | Group education: By brief 3‐h social event about optimal BF practices once at third trimester pregnancy |
|
|
||
| 2 |
|
|
| 3 |
|
|
During a prenatal or postnatal time, Health Extension Workers (HEW) offered the Control Group (CG) with usual care, which includes standard breastfeeding support. The Health Extension Workers (HEW) programme strategy of the Ethiopian Ministry of Health states that HEWs are certified female graduates who are trained and assigned to serve at the local health post at the kebele (Ethiopia's lowest administrative unit) level. With the assistance of healthcare professionals from local healthcare facilities, HEW offers mothers health‐post‐based IYCF counselling and education, including breastfeeding, through the pregnant and lactating mother's forum (IYCF is one of the packages of health and nutrition interventions). The content of the education, printed materials, and home visits were prepared based on IYCF guidelines and Essential Nutrition Action guidelines (ENA) and provided to the intervention group. Therefore, the content provided by HEW to the control groups was also similar to the content the intervention group received from health care providers who work near health institutions. As part of our study design, HEW routinely provided breastfeeding education and counselling to mothers in the control group; this is regarded as an intervention given to the mothers alone.
2.3.2. Data Collection Method
Data were collected by 16 data collectors through a face‐to‐face interview by trained nurses or midwives who were working in the nearby health centre for a specific cluster and had not participated in the intervention. Data on both child‐related characteristics and frequency of child morbidity were collected 6 months after delivery. Single‐blinding was implemented, meaning that the outcome assessors (data collectors) were unaware of the assigned intervention.
2.4. Outcome Measures
The frequency of morbidity in children was measured by assessing three specific conditions: diarrhoea, fever, and acute respiratory illnesses (ARIs). The study utilized the following questions to determine the presence of these morbidities: Has the child experienced diarrhoea in the last 6 months? Secondly, has the child experienced any fever in the past 6 months? Thirdly, has the child experienced a cough accompanied by difficulty breathing or breathing more quickly than a normal illness within the previous 6 months? If so, how many times? The frequency of these three morbidities over the 6‐month period was then summed to obtain the dependent variable, which represents the total frequency of morbidity in children during the post‐delivery period measured as count (0, 1, 2…). 0 represents the absence of any one of the three morbidity conditions (true zero). 1 represents at least one condition happening once. 2 represents at least one condition happening twice or two conditions happening one time for each. The same is true for subsequent numbers.
2.5. Data Analysis
The data were entered into Epi Data 3.1 and analysed using SPSS for Windows version 23 and STATA 14. The variance (3.134) was found to be greater than the mean (1.85), indicating that there is evidence of over‐dispersion (assumption violated), which suggests fitting an alternative count data regression model. Then a negative binomial model was fitted to account for over‐dispersion. The negative binomial model addresses the issue of over‐dispersion by including a dispersion parameter to accommodate the unobserved heterogeneity in the count data. In this study, the frequency of child morbidity data experienced excess zeros characterized by over‐dispersion. Thus, the negative binomial model cannot address the over‐dispersion caused by an excessive number of zeros. In such cases, the zero‐inflated negative binomial (ZINB) model is highly appropriate because it mixes a count component and a point mass at zero, controlling for over‐dispersion [26].
Furthermore, log pseudo‐likelihood, AIC, and BIC, including the offset variable (ID), were used to compare various candidate models, and the model with the smallest AIC and BIC and the highest log pseudo‐likelihood value was considered a better fit [27]. Therefore, ZINB is a better fit model for this data than other models. Incident rate ratio with its 95% confidence interval and a p < 0.05 were used to report the strength.
2.5.1. Ethics Approval and Consent to Participate
Letters of ethical approval were obtained from the Wachemo University Research Ethics Committee (WCUREC) (reference number WCU. RE. Dev. Di/010/2015) and the Jimma University Institutional Review Board (JUIRB) (reference number JUIRB37/22). All participants were informed about the study's objectives, and written informed consent was obtained. During the data collection and intervention periods, data collectors were given a face mask and sanitizer as part of the COVID‐19 infection protection measures. The study was carried out in compliance with the Declaration of Helsinki's international guidelines.
3. Results
At baseline, a total of 408 eligible couples were recruited in the intervention (n = 204) and control groups (n = 204). After 9 months of follow‐up, 3 couples in the intervention group and 3 in the control group refused to participate; 5 couples (1 from the intervention and 4 from the control group) were lost due to migration, and 1 couple in the control group was not contacted due to stillbirths. Overall, end‐line data were completed for 397 (97.3%) of the study participants in both study groups (Figure 1).
Figure 1.
Trial flow‐diagram.
The baseline couples' demographic and socio‐economic characteristics did not show any significant differences between the intervention and control groups. Regarding childbirth‐related factors, 350 (88.16%) had normal birth weight, and 47 (11.84%) had low birth weight, and 210 (52.9%) were male and 187 (47.1%) were female. Other child‐related characteristics are displayed in Table 2.
Table 2.
The maternal and new‐borns characteristics after delivery.
| Variables | Category | Intervention N (%) | Control N (%) |
|---|---|---|---|
| Sex of child | Male | 106 (50.5%) | 104 (49.5%) |
| Female | 94 (50.3%) | 93 (49.7%) | |
| Birth weight | ≥ 2500 g | 175 (50%) | 175 (50%) |
| < 2500 g | 25 (53.2%) | 22 (46.8%) | |
| Birth order | 1st | 33 (49.2%) | 32 (50.8%) |
| 2nd | 26 (54.2%) | 22 (45.8%) | |
| 3rd | 36 (54.5%) | 30 (45.5%) | |
| 4th and above | 105 (48.2%) | 13 (51.8%) | |
| Mode of delivery | SVD | 180 (51.7%) | 168 (48.3%) |
| C/S | 20 (40.8%) | 29 (59.2%) | |
| Who assist the delivery | Health professional | 187 (54.4%) | 157 (45.6%) |
| TBA | 13 (24.5%) | 40 (75.5%) | |
| Place of birth | Home | 22 (37.3%) | 37 (62.7%) |
| Hospital | 81 (49.4%) | 83 (50.6%) | |
| Health centre | 97 (55.7%) | 77 (44.3%) |
In the 6‐month follow‐up, 34.5% of infants remained healthy with no episodes of illness. The highest morbidity level recorded was six episodes per child, which occurred in 3.53% of the children. Over‐dispersion of the mean (1.85) and variance (3.134) was observed (Figure 2).
Figure 2.
Frequency distribution of child morbidity in central Ethiopia.
3.1. Effects of the Intervention
Potential child‐related confounding variables were tested for significance with frequency of child morbidity in bivariate zero‐inflated negative binomial regression analysis.
Binary zero‐inflated negative binomial regression analysis showed no difference in the frequency of child morbidity by gender of the child, birth weight of the child, and order of birth. Therefore, only the crude result of the intervention was considered. Accordingly, children whose mother and father received optimal breastfeeding promotion interventions had a 92.7% (IRR = 0.073, 95% CI: 0.039–0.138, p < 0.001) lower incidence rate of morbidity as compared to children whose mother received routine care during the intervention period (Table 3).
Table 3.
ZINB regression model for the frequency of children morbidity in central Ethiopia.
| Variable | Category | SE | Z‐value | IRR | 95% CI for IRR | p | |
|---|---|---|---|---|---|---|---|
| Study group | Intervention | 0.023 | −8.07 | 0.073 | 0.039 | 0.138 | < 0.001 |
| Ref: control | |||||||
| SEX of child | Female | 0.325 | −0.63 | 0.767 | 0.333 | 1.763 | 0.53 |
| Ref: male | |||||||
| birth weight | > 2500 g | 0.450 | −0.25 | 0.879 | 0.323 | 2.399 | 0.80 |
| Ref: < 2500 g | |||||||
| Order of birth | Ref: 1st | ||||||
| 2nd | 2.039 | 0.79 | 2.129 | 0.326 | 13.915 | 0.43 | |
| 3rd | 1.390 | 0.36 | 1.419 | 0.208 | 9.682 | 0.72 | |
| 4th and above | 1.132 | 0.38 | 1.369 | 0.271 | 6.922 | 0.70 | |
4. Discussion
The present study aimed to evaluate the effect of couple‐based optimal breastfeeding promotion and support on child morbidity within 6 months post‐delivery. The finding highlighted the protective effects of couple‐based optimal breastfeeding promotion intervention against the frequency of child morbidity.
In the present study, children whose mother and father received optimal breastfeeding promotion and support interventions had a 92.7% lower incidence rate of morbidity as compared to children whose mother received routine care during the intervention period. The results indicate that couple‐based optimal breastfeeding educational interventions have a protective effect on child morbidity as compared to routine care. This finding is consistent with a population‐based study done in the United Kingdom, which revealed that exclusive breastfeeding, compared with not breastfeeding, protects against hospitalization for diarrhoea and lower respiratory tract infection [28], and an eight‐country cohort study shows that exclusive breastfeeding 0–6 months was protective against diarrhoea and acute lower respiratory infections (ALRI). Fever was a consistent risk factor for both diarrhoea and ALRI [29]. A study done in Vietnam has also shown that early initiation and exclusive breastfeeding protect against diarrhoea and ARI [30]. Similarly, exclusively breastfed infants had lower odds of having an illness with a cough, fever, and diarrhoea compared to non‐exclusively breastfed infants [31].
Systematic reviews/meta‐analyses revealed that breastfeeding was associated with a reduction in the risk of acute otitis media, non‐specific gastroenteritis, severe lower respiratory tract infections, atopic dermatitis, asthma (young children), obesity, and type 1 and 2 diabetes [5, 32, 33]. In addition, two systematic reviews found that a lack of exclusive breastfeeding among infants 0–5 months of age and no breastfeeding among children 6–23 months of age is associated with increased diarrhoeal morbidity and mortality and that suboptimal breastfeeding elevated the risk of pneumonia morbidity and mortality outcomes across age groups (0–23 months) in low‐ and middle‐income countries [34, 35]. This study further expands by adding acute respiratory illnesses (ARIs) upon the evidence base established by Lamberti et al. [34], who predominantly looked at diarrhoea and pneumonia.
However, our study contrasts with a cluster randomized controlled trial done in a rural district of Burkina Faso to evaluate the effect of maternal and child nutrition counselling interventions, including breastfeeding, on the cumulative incidence of diarrhoea, fever, and acute respiratory infection; no significant differences were found in child morbidity [36]. The differences between the current study and the aforementioned study may be attributed to the differences between the interventions provided to mother‐father pairs in our study, unlike the aforementioned study that provided for mother‐child pairs.
This couple‐based intervention study was designed and applied based on social cognitive theory [25]. It used the ideas of teaching the support groups around the breastfeeding mother, like spouses, which changed the mother's desire to breastfeed optimally and changed the way she practiced optimal breastfeeding [16]. The changes of the fathers' knowledge, attitude, and practices as well as the intention of the mother toward optimal breastfeeding may provide additional information on the ways the intervention affects mothers' optimal breastfeeding practices.
The strength of our study was the use of a cluster randomized control trial to compare the frequency of child morbidity over a 6‐month follow‐up period in a rural community setting. The second strength of our trial was providing couple‐based breastfeeding intervention both in the prenatal and postnatal periods with different intervention approaches and another strength was low attrition during follow‐up; nevertheless, there are a few limitations that deserve mention here. First, this trial was conducted in a small geographic area, and representation from two districts in one geographic region limits the generalizability of study results. Secondly, the 6‐month child morbidity experiences were assessed based on recall since birth. Therefore, all child morbidity relied on maternal recall and was not based on direct observation, so even though we try to prove mothers recall, we cannot exclude the possibility that mothers in the trial might have exhibited recall bias. Despite the aforementioned potential limitations, the findings from this study replicate the findings from previous studies that strengthen the existing evidence on the importance of couple‐based breastfeeding promotion intervention in the area of child health services. Future research would benefit from expanding an intervention to other community influencing factors like economic factors and health related factors in addition to social support system like family support. We recommend policy makers scale up the involvement of male partners during optimal breastfeeding promotion into existing child and maternal health services based on different socio‐cultural contexts.
5. Conclusions
The couple‐based optimal breastfeeding promotion and support intervention has shown a protective effect against the frequency of child morbidity, highlighting the desirability of providing optimal support that includes the father in the community settings.
Author Contributions
Mulatu Abageda, Tefera Belachew, Zeleke Dutamo Agde, Worku Abageda Anamo and Belayneh Hamdela Jena wrote the first draft, participated in the trial design, and reviewed subsequent drafts leading to the final manuscript. Mulatu Abageda wrote the original draft. Mulatu Abageda, Belayneh Hamdela, Zeleke Dutamo Agde, Worku Abageda Anamo and Tefera Belachew reviewed the final draft of the manuscript. All authors have read and approved the final version of the manuscript and Mulatu Abageda as corresponding author or manuscript guarantor had full access to all of the data in this study and takes complete responsibility for the integrity of the data and the accuracy of the data analysis.
Conflicts of Interest
The authors declare no conflicts of interest.
Transparency Statement
The lead author Mulatu Abageda affirms that this manuscript is an honest, accurate, and transparent account of the study being reported; that no important aspects of the study have been omitted; and that any discrepancies from the study as planned (and, if relevant, registered) have been explained.
Acknowledgments
The study sponsors and funders have no role in the design of the study, the collection, analysis, and interpretation of data, or the writing of the manuscript. The authors would like to express their gratitude for the financial support provided by the Nestlé Foundation for the study of problems of nutrition in the world, Lausanne, Switzerland, and Jimma University without award/grant number (N/A).
Data Availability Statement
The datasets supporting the conclusion of this study are available upon reasonable request from the corresponding author.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The datasets supporting the conclusion of this study are available upon reasonable request from the corresponding author.