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Behaviour change interventions improve maternal and child nutrition in sub-Saharan Africa: A systematic review

  • Daniella Watson ,

    Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Resources, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing

    Affiliations Global Health Research Institute, Human Development and Health, Faculty of Medicine, University of Southampton, Southampton, United Kingdom, Department of Global Health and Social Medicine, King’s College London, London, United Kingdom, SAMRC Developmental Pathways for Health Research Unit, School of Clinical Medicine, University of the Witwatersrand, Johannesburg, South Africa

  • Patience Mushamiri,

    Roles Formal analysis, Validation, Writing – review & editing

    Affiliation SAMRC Centre for Health Economics and Decision Science, PRICELESS, University of the Witwatersrand, School of Public Health, Faculty of Health Sciences, Johannesburg, South Africa

  • Paula Beeri,

    Roles Formal analysis, Investigation, Writing – review & editing

    Affiliation Navrongo Health Research Centre, Ghana Health Service, Accra, Ghana

  • Toussaint Rouamba,

    Roles Formal analysis, Investigation, Writing – review & editing

    Affiliation Clinical Research Unit of Nanoro, Institute for Research in Health Sciences, National Center for Scientific and Technological Research, Ouagadougou, Burkina Faso

  • Sarah Jenner,

    Roles Formal analysis, Methodology, Writing – review & editing

    Affiliation Medical Research Council Lifecourse Epidemiology Centre, University of Southampton, Southampton, United Kingdom

  • Simone Proebstl,

    Roles Formal analysis, Methodology, Writing – review & editing

    Affiliations Medical Research Council Lifecourse Epidemiology Centre, University of Southampton, Southampton, United Kingdom, Institute for Medical Information Processing, Biometry, and Epidemiology—IBE, LMU Munich, Munich, Germany, Pettenkofer School of Public Health, Munich, Germany

  • Sarah H Kehoe,

    Roles Conceptualization, Writing – review & editing

    Affiliations Global Health Research Institute, Human Development and Health, Faculty of Medicine, University of Southampton, Southampton, United Kingdom, Medical Research Council Lifecourse Epidemiology Centre, University of Southampton, Southampton, United Kingdom

  • Kate A Ward,

    Roles Conceptualization, Writing – review & editing

    Affiliations Global Health Research Institute, Human Development and Health, Faculty of Medicine, University of Southampton, Southampton, United Kingdom, Medical Research Council Lifecourse Epidemiology Centre, University of Southampton, Southampton, United Kingdom, School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa

  • Mary Barker,

    Roles Conceptualization, Methodology, Supervision, Writing – review & editing

    Affiliations Medical Research Council Lifecourse Epidemiology Centre, University of Southampton, Southampton, United Kingdom, School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa, NIHR Southampton Biomedical Research Centre, University Hospitals Southampton NHS Foundation Trust, Cambridge, United Kingdom, School of Health Sciences, Faculty of Life and Environmental Sciences, University of Southampton, Southampton, United Kingdom

  • Wendy Lawrence,

    Roles Conceptualization, Methodology, Supervision, Writing – review & editing

    Affiliations Medical Research Council Lifecourse Epidemiology Centre, University of Southampton, Southampton, United Kingdom, NIHR Southampton Biomedical Research Centre, University Hospitals Southampton NHS Foundation Trust, Cambridge, United Kingdom

  • the INPreP Study Group

    Membership of INPreP Study Group is provided in the Acknowledgments.


Evidence that nutrition-specific and nutrition-sensitive interventions can improve maternal and child nutrition status in sub-Saharan Africa is inconclusive. Using behaviour change theory and techniques in intervention design may increase effectiveness and make outcomes more predictable. This systematic review aimed to determine whether interventions that included behaviour change functions were effective. Six databases were searched systematically, using MeSH and free-text terms, for articles describing nutrition-specific and nutrition-sensitive behaviour change interventions published in English until January 2022. Titles, abstracts and full-text papers were double-screened. Data extraction and quality assessments followed Centre for Reviews and Dissemination guidelines. Behaviour change functions of interventions were mapped onto the COM-B model and Behaviour Change Wheel. PROSPERO registered (135054). The search yielded 1193 articles: 79 articles met inclusion criteria, ranging from low (n = 30) to high (n = 11) risk of bias. Many that applied behaviour change theory, communication or counselling resulted in significant improvements in infant stunting and wasting, household dietary intake and maternal psychosocial measures. Interventions with >2 behaviour change functions (including persuasion, incentivisation, environmental restructuring) were the most effective. We recommend incorporating behaviour change functions in nutrition interventions to improve maternal and child outcomes, specifically drawing on the Behaviour Change Wheel, COM-B model (SORT B recommendation). To enhance the designs of these interventions, and ultimately improve the nutritional and psychosocial outcomes for mothers and infants in sub-Saharan Africa, collaborations are recommended between behaviour change and nutrition experts, intervention designers, policy makers and commissioners to fund and roll-out multicomponent behaviour change interventions.


The triple burden of malnutrition [1], coexistence of under- and over-nutrition [2] and poor micronutrient status impacts maternal and child health [36]. In sub-Saharan Africa this occurs at the household level, where family members can be underweight (BMI<18.5kg/m²) [7] or overweight (BMI>25kg/m²) [7], and at the individual level, where an infant can be stunted (height for age < -2 SD from the median) [7], wasted (weight for age <-2SD from the median) [7] or overweight [8]. One meta-analysis found that rural residency, low educational status of partners, multiple pregnancies and poor nutritional indicators were determinants of malnutrition in pregnancy [9]. A recent Lancet series [36, 1017] advocated for person-centred health systems and proposed a lifecourse double-duty approach to optimise dietary quality to address both under- and over-nutrition [1114]. They advise using both “nutrition-specific” and “nutrition-sensitive” interventions [36]. Large-scale nutrition-sensitive interventions (agriculture, clean water, sanitation, education and employment) may enhance nutrition-specific interventions (breastfeeding promotion, fortification of foods, and micronutrient supplementation) by addressing underlying determinants of nutrition [5, 18]. Approaches to improve infant nutrition status include 1) promotion of individual behaviour change to address diet quality, 2) food fortification, 3) nutritional supplementation [1820].

Behavioural functions of interventions are increasingly recognised as crucial, yet expertise in global health behaviour change is lacking [21]. Shelton (2013) described behaviour change as the missing block in global health systems, pointing out that the top 20 health risks (e.g. obesity, childhood underweight, vitamin deficiencies) in sub-Saharan Africa are influenced by behaviour (e.g. care seeking, adherence, pro-social behaviours) [21]. Public health and health promotion interventions based on social and behavioural science theories are more effective than interventions without such a theoretical base [22]. Further, a lack of theory-informed evaluations limits what can be learnt about how interventions work in different contexts, how health impacts are observed, and effects on primary and secondary outcomes [2325].

Research suggests that intervention strategies must combine behaviour change with access to nutritious food [26], acknowledging that people eat ‘food’ rather than ‘nutrients’ [27]. Behavioural scientists and health psychologists argue that those designing behaviour change interventions should engage with the target population, understand their motivation to change, and adapt interventions to the contexts that facilitate change including environment and social networks [26]. One model used by Health Psychologists is the Behaviour Change Wheel (Fig 1) which encapsulates features applicable to intervention design and implementation [28]. It outlines nine behavioural intervention functions, that aims to address deficits in one or more of the three underlying human factors–Capability (physical and psychological), Opportunity (physical and social), and Motivation (automatic and reflective) that influence Behaviour (COM-B model) (Fig 2). Both models can be applied to inform the design of interventions to improve maternal and child nutrition in the context into which they are being implemented.

Fig 2. The COM-B model (capability, motivation, opportunity–behaviour) (Michie et al, 2011) [28].

A systematic review was undertaken to collate evidence to answer the following questions: 1) are behaviour change nutrition- interventions effective in improving maternal and child nutrition in sub-Saharan? 2) which functions of behaviour change interventions are associated with improvements in maternal and child nutrition outcomes?

Materials and method

Search strategy and study selection

This systematic review follows the Centre for Reviews and Dissemination [29] and PRISMA guidelines (S1 Checklist) [30, 31]. It is PROSPERO registered (135054). Articles were systematically searched for on major medical and social science databases including Cochrane library, EMBASE, MEDLINE, PSYCHINFO, CINAHL and African Journal OnLine (AJOL) published up to 1st November 2022. The search strategy was based on the most prevalent behaviour change concepts and theories identified by Davis et al (2015) [32]. Nutrition-specific and nutrition-sensitive interventions, and maternal and child nutrition terms were derived from the 2013 Lancet series on Maternal and Child Nutrition [4, 5] and in consultation with experts. The terms were entered into the databases using a combination of Medical Subject Headings (MeSH) and free text to include behaviour change interventions for maternal and child nutrition in sub-Saharan Africa (S1 Table). The terms were based on English and American spelling and were not translated into other languages. Further studies were sought by hand-searching bibliographies of included studies, tracking citations on Google Scholar, and asking experts on the topic. Breastfeeding interventions were excluded as there have been previous systematic reviews on this topic, which incidentally conclude that evidence for including behaviour change in breastfeeding and complimentary feeding interventions is lacking [33, 34].

Publications were stored in Endnote X9.2, duplications were removed and papers were screened on Rayyan qcri online website [35]. Paper titles, abstracts and full text were double-screened. Inclusion criteria can be found in Tables 1 and S2. Full texts were screened by a Health Psychologist to select only interventions that had a behaviour change component and analyse the findings using the Behaviour Change Wheel [28] (S3 Table). Discrepancies were resolved by team review, which was deemed the final consensus.

Table 1. Systematic review inclusion and exclusion criteria.

Data extraction and quality assessment

Data were extracted by two independent researchers to create Table 3. The table describes all interventions which were categorised by the number of Behaviour Change Intervention Functions identified, by risk of bias score and publication date. Study designs were coded using an established method [36] based on the functions from the Behaviour Change Wheel and coded to the COM-B model [28]. This is a well-evidenced behaviour change framework and this type of analysis has been carried out in other research studies [28]. Each intervention was reviewed independently by two trainee Health Psychologists, who identified which Behaviour Change Wheel intervention functions were included in each intervention, under the supervision of a chartered Health Psychologist. The results section was structured around the main nutrition, psychosocial and behavioural outcomes, as advised by a nutritionist expert. Studies that included one of these outcomes were described under the appropriate heading.

A quality assessment tool was adapted from a systematic review on digital interventions using mixed methods and tailored for use in this review (S4 and S5 Tables) [37], based on the Centre for Reviews and Dissemination quality assessment criteria [29]. Papers were assessed for risk of bias by two reviewers independently (Table 2). Scores between -4 and 4 indicated a medium risk of bias. Scores below—4 and above 4 indicated a high and low risk of bias respectively.

Data synthesis

As there were different effect measures used across studies, a meta-analysis was not appropriate. Instead we conducted vote counting based on the direction of effect, as advised by the Synthesis Without Meta-analysis (SWiM) reporting guidelines (S2 Checklist) [38] and the Cochrane handbook for systematic reviews of interventions [39]. Cochrane’s most recent advice for accurate vote counting was to consider the direction, not the significance, of each intervention’s effect estimates in terms of showing a health benefit or harm, in order to produce a standardised binary metric. To determine if an intervention showed a health benefit or harm, we hypothesised that behaviour change nutrition interventions would improve maternal and child nutrition and psychosocial outcomes in communities in sub-Saharan Africa. A health benefit would include, for example, interventions that reduced infant stunting and wasting, increased the quality and quantity of household foods being eaten and improved mother’s and family’s psychological capabilities to feed their children. Each outcome from each paper was classified as either positive (supports the hypothesis–health benefit), negative (rejects the hypothesis–health harm) or as inconclusive if outcome could not be determined. The vote-counting results were summarized visually using an effect direction plot. Arrows were used to represent the combined direction for each study and outcome in the effect direction plot. Based on previous criteria [39], more than 70% of positive outcomes were interpreted as overall positive (↑), and studies with more than 70% of negative outcomes as overall negative (↓), whereas less than 70% of either positive or negative outcomes within one outcome category were interpreted as inconclusive (↔). Studies were excluded from vote counting if they did not demonstrate statistical evidence to answer the hypothesis including process evaluations and qualitative studies, and also studies graded as high risk of bias. Within studies, outcomes that could be interpreted ambiguously as to whether this was a benefit or harm within the context, for example increased use of oil, were also excluded. Each outcome was categorised into one of four overarching categories: 1) anthropometric markers, 2) dietary outcomes, 3) psychosocial outcomes, 4) other outcomes. Anthropometric markers included measure of infant body composition such as weight-age-Z scores (HAZ), weight-height-Z scores (WHZ), weight-age-Z scores (WAZ). Dietary outcomes included potential changes related to a variety of individual and household dietary diversity measures and food items consumed. Psychosocial outcomes included potential changes in nutrition knowledge, practice, self-efficacy and developmental outcomes. Other outcomes encompassed outcomes that indirectly influence nutrition such as prevalence of infectious disease, behaviours related to hygiene and economic and agricultural indicators.

Results are presented as a narrative synthesis [40] and based on the intervention’s quality assessment and direction of effect in relation to research question one. Each finding from a study reports the risk of bias score (RoB) and direction of effect (DE) in brackets to accompany the description. The Strength of Recommendation Taxonomy (SORT) was used to appraise the overall quality, quantity and consistency of evidence and provide a grading for the recommendations of this review [41]. Tables 3 and 4 report the descriptions of each paper, the risk of bias score and the direction effect according to the hypothesis.

Table 3. Descriptions of included studies found in the systematic review.


1193 papers were identified leaving 995 studies after duplicates were removed to be screened by titles and abstracts. From this screening, 158 papers were eligible to progress to full text screening. Twenty-three further articles, eight new interventions studies and 15 papers related to studies already included in this review, were found during the bibliography search and expert consultation. A total of 79 articles were included (Fig 3).

The 79 articles were published between 2004–2022 and included cluster randomised control trials (RCT)(n = 38) [20, 4278], quantitative studies(n = 17) [7999], study evaluations(n = 13) [55, 58, 69, 100110], mixed methods studies(n = 5) [80, 81, 111113], qualitative studies(n = 4) [114117], and national case studies(n = 2) [118, 119]. Behaviour change interventions were identified from 18 sub-Saharan African countries: Ethiopia(n = 19) [45, 60, 61, 64, 66, 68, 69, 71, 8487, 92, 96, 103105], Malawi(n = 10) [46, 47, 72, 78, 101, 102, 106, 109, 116, 117], South Africa(n = 8) [43, 44, 48, 49, 67, 7981], Kenya(n = 5) [42, 88, 111, 112, 114], Burundi(n = 5) [5155], Nigeria(n = 6) [74, 82, 89, 91, 93, 115], Burkina Faso(n = 6) [51, 57, 58, 75, 77, 120], Ghana(n = 4) [83, 108, 119],Tanzania(n = 3) [50, 73, 94], Madagascar(n = 2) [20, 76], Zambia(n = 2) [99, 107], Senegal(n = 2) [95, 113] and one each from, Central African Republic [118], Mali [65], Mozambique [98], Rwanda [70], Togo [63], and Uganda [56]. One study included findings from four countries including Burkina Faso, Tanzania, Senegal, and Cote d’Ivoire [97]. A total of 30 studies were graded as low risk of bias, 38 as medium, and 11 as high (Table 2). Studies were not removed if they were deemed low quality as findings might still have been informative providing novel evidence on using behaviour change and nutrition components together in an intervention, accepting that there was some bias in the intervention design. This was accounted for in the analysis and discussion of this paper. However, all findings are presented alongside their risk of bias to highlight which studies’ findings may be less credible. The studies deemed as low quality are not given as much weight in this review due to the possible bias and accuracy of results and interpretation. Studies of low quality were not included in the vote counting analysis (Table 4).

Descriptions of intervention design, outcomes and implications are presented in Table 3. The results are summarised below by the impact the interventions had on 1) anthropometric markers, 2) dietary outcomes, 3) psychosocial outcomes and 4) behavioural intervention components. Using SORT to grade the recommendations, we conclude that the use of behaviour change components within nutrition interventions improves maternal and child nutrition and psychosocial outcomes. Our recommendation is graded as SORT B due to: the use of a variety of study designs including RCTs, evaluations, quantitative and qualitative studies; a range of low-high risk of bias; and the direction of effect of studies to meet the hypothesis [41].

Anthropometric markers

Overall, there was evidence showing that behaviour change nutrition interventions have an effect on anthropometric markers such as height and weight. Nineteen out of the 25 studies favoured the intervention (76% [57%,89%], p = 0.015); 16 out of the 25 studies were of low risk of bias. Out of these, 13 favoured the intervention.

A mother and child lipid supplementation RCT combined with maternal nutrition counselling in Madagascar reported an increase in infants’ length-for-age z-scores (LAZ) of 0.210–0.216SD and stunting reduced by 8.2–9.0% compared to the control (RoB = Medium, DE = ↑ [76]; RoB = Low, DE = ↔ [20]). Similar interventions in Malawi found mixed results, where one intervention had no effect on infant LAZ scores or stunting prevalence, but both interventions found significantly higher weight-for-length z-score (WLZ) and mid-upper arm circumference at 18 months to three years follow-up (RoB = Medium, DE = N/A [102]; RoB = High, DE = N/A) [101]; RoB = High, DE = N/A) [106]; RoB = Medium, DE = ↑ [109]). These results have to be viewed with caution, however, since the trial was low quality being not randomised or blinded. Interventions that provided food rations or vouchers and behaviour change communication to mothers in Burundi and Ethiopia, showed reduced prevalence of child stunting in the intervention compared to the control arm (RoB = Low, DE = ↑ [51, 53, 71]).

An agricultural production and behaviour change communication intervention for mothers in Burkina Faso significantly improved child wasting, diarrhoea, haemoglobin levels and rates of anaemia, especially among the youngest, as well as reducing underweight prevalence (RoB = Low, DE = ↔ [57]; RoB = Low, DE = ↑ [58]). One chicken production intervention improved infant HAZ and weight-for-age z-scores (WAZ) both with and without behaviour change communication in Ethiopia (RoB = Low, DE = ↑ [66]). An agricultural (tools and agricultural extension workers), behaviour change communication and nutrition counselling intervention in Ethiopia reduced prevalence of stunting (36.3% to 22.8%) in children aged 6–23 months(RoB = Low, DE = ↑ [69];RoB = Medium, DE = ↔) [100]. One RCT that trained local Tanzanian women and farmers to deliver agricultural education to households as well as them receiving seedlings did not find significantly improved infant HAZs and WHZs scores RoB = Low, DE = ↔) [73].

Dietary outcomes

There was evidence that behaviour change nutrition interventions influence dietary outcomes, with 34 out of 46 studies favouring the intervention (74% [60%, 84%], p = 0.002). Twenty-three studies were judged to be at a low risk of bias, and 18 of these favoured the intervention.

Two behaviour change communication interventions increased maternal dietary diversity in Ethiopia(RoB = Medium, DE = ↔ [103]; RoB = Medium, DE = ↑) [104]) and in Burundi (RoB = Low, DE = ↔ [51]; RoB = Low, DE = ↑ [52]). One behaviour change communication RCT found increased infant consumption of milk, but this was not significant (RoB = Medium, DE = ↓ [70]). Two interventions based on nutrition education found small yet insignificant changes in the nutrient intake of children in Malawi (RoB = Low, DE = ↑ [46, 47]) and South Africa(RoB = Medium, DE = ↑ [80]; RoB = Medium, DE = N/A [81]). Yet one RCT found significant infant dietary diversity improvement with a combined nutrition education and counselling approach in Malawi (RoB = Medium, DE = ↑ [72, 78]). One intervention underpinned by Social Cognitive Theory and the Theory of Planned Behaviour had school children in South Africa meeting 5-a-day fruit and vegetable guidelines (RoB = Low, DE = ↑ [48, 49]).

Two psychosocial interventions increased pregnant women’s and mothers’ dietary diversity, and household food consumption in the Central African Republic (RoB = High, DE = N/A [118]) and Ethiopia (RoB = Medium, DE = ↑ [104]; RoB = Medium, DE = ↔ [103]). A intervention that delivered radio dramas on maternal nutrition in Ghana found improved infant dietary diversity (RoB = High, DE = N/A [110]). One RCT that trained local Tanzanian women and farmers to deliver agricultural education to households as well as them receiving seedlings found significantly improved infant dietary diversity and food insecurity (RoB = Low, DE = ↑ [73]).

Psychosocial outcomes

We found evidence that interventions including behaviour change functions have an effect on psychosocial outcomes, with 27 out of 33 studies favouring the intervention (82% [66%, 91%], p < 0.001). Sixteen studies had a low risk of bias, of which 15 favoured the intervention.

Interventions aimed to address psychosocial outcomes including nutrition knowledge (n = 17) [4345, 4749, 60, 63, 72, 74, 82, 86, 88, 89, 108, 113, 114], practices (e.g. food/recipes preparation)(n = 5) [45, 82, 86, 88, 90], attitudes (n = 6) [45, 48, 49, 64, 82, 86], intentions (n = 4) [48, 49, 64, 91] and confidence in eating healthy food (n = 1) [114]. These were variously underpinned by behaviour change theory(n = 10) [45, 48, 49, 60, 64, 82, 86, 88, 90, 108], strategies to increase self-efficacy (n = 5) [4345, 79, 91], behaviour change communication (n = 2) [47, 63] or behaviour change techniques (n = 1) [89].

In two interventions women’s capability to feed themselves and their children more nutritious food increased, including interventions based on behaviour change communication in Burkina Faso (RoB = Low, DE = ↑ [57, 58]) and Zambia (RoB = Low, DE = ↑ [107]), and a psychosocial intervention in Ghana (RoB = High, DE = N/A [83]). Five psychosocial interventions achieved positive psychosocial outcomes, which improved caregiver feeding behaviours. This included increasing women’s psychological well-being in the Central African Republic (RoB = High, DE = N/A [118]) and Uganda (RoB = Medium, DE = ↑ [56]). Caregivers of children with cerebral palsy in Tanzania improved their feeding skills (RoB = Low, DE = ↑ [50]). Caregiver relationships and communication improved leading to children’s prosocial behaviour in Mozambique (RoB = Medium, DE = ↑ [98]). An intervention which delivered radio dramas on maternal nutrition in Ghana found increased mother’s knowledge of feeding practices (RoB = High, DE = N/A [110]). Qualitative evaluations identified barriers to the success of behavioural interventions including availability of, and access to, nutritious and affordable foods and less time for mothers to care for children (RoB = High, DE = N/A [116]).

Behavioural intervention components

Interventions were coded on the basis of involving one or more Behaviour Change Wheel intervention functions (Fig 1) [28]. Functions (S3 Table) included education(n = 56) [20, 4244, 4750, 52, 5457, 58, 60, 7081, 83, 84, 87, 8994, 103105, 107112, 115121], enablement(n = 56) [20, 42, 4750, 52, 5457, 58, 6172, 7582, 85, 86, 8991, 93, 94, 96, 98107, 109, 113115, 117, 119121], persuasion(n = 46) [42, 52, 54, 55, 57, 58, 6266, 6873, 75, 77, 78, 8890, 9297, 99102, 106, 107, 110, 113, 117, 119121], training(n = 39) [20, 4245, 4850, 57, 58, 61, 63, 67, 70, 71, 73, 7577, 79, 8286, 91, 93, 9799, 101, 102, 106, 108, 111115, 120], modelling(n = 39) [43, 44, 48, 49, 57, 58, 61, 6769, 7173, 75, 77, 78, 87, 92, 9698, 100, 110112, 117, 120], environmental restructuring (n = 17) [45, 47, 50, 57, 58, 66, 68, 69, 73, 77, 82, 96, 97, 99, 100, 116, 120], incentivisation (n = 11) [63, 65, 71, 73, 84, 85, 89, 111, 116, 118]. There were no interventions that included restriction or coercion. Table 5 indicates that in interventions where the Behaviour Change Wheel intervention functions persuasion, environmental restructuring and incentivisation were used, body composition and diet intake improved.

Table 5. The numbers of interventions using Behaviour Change Wheel intervention functions and the percentage of those where outcomes improved, did not improve or were not measured.

Education, enablement and training appeared to have less impact on these maternal and infant body composition and diet intake outcomes. However, psychosocial outcomes seemed to improve in interventions with training, incentivisation, modelling and education functions, and less so in interventions which included enablement such as nutrient supplementation. Interventions with multiple Behaviour Change Wheel intervention functions tended also to be those that improved maternal and child nutrition and health outcomes. The optimal number of intervention functions is not possible to determine because so few of the interventions had more than three. Our ability to draw conclusions about the effectiveness of intervention functions is limited by the fact that many of the studies do not measure all outcomes; measurements of nutritional intake are often omitted.

Table 6 describes the way in which people’s capability, opportunity and motivation are addressed in interventions to improve maternal and child nutrition and health outcomes. For example, food demonstrations and provision of agricultural land address physical capability and opportunity components respectively as specified by the COM-B model as necessary to change behaviour.

Table 6. The categories of studies’ intervention components analysed to the COM-B model.


This review of 79 studies addressed the question of whether nutrition-specific and nutrition-sensitive interventions were effective in improving maternal and child nutrition outcomes in sub-Saharan Africa if they included behaviour change functions. It was found that those that were based on behaviour change theory, counselling and communication, produced the most significant positive impacts on infant and children nutrition outcomes. This included reduced prevalence of wasting, underweight and stunting, and improved diet outcomes including dietary diversity and total food consumption. There is little evidence that these interventions improved maternal and infant nutrient intake. This could be because changes in nutrient intake were not often measured due to a lack of comprehensive data on the nutrient composition of foods. These interventions reviewed also identified improvements in maternal psychosocial outcomes in relation to nutrition, including knowledge, practice, attitude, intention, confidence, capability and wellbeing.

Interventions which included the Behaviour Change Wheel intervention functions, i.e. incentivisation, persuasion and environmental restructuring, tended to be those that improved maternal and child nutrition and psychosocial outcomes. The COM-B model suggests that not addressing participant’s motivation reduces the effectiveness of behaviour change interventions. This analysis in Table 6 demonstrates that nutrition-specific and nutrition-sensitive interventions cannot alone address motivation and require additional behaviour change functions in order to address behaviours that improve maternal and child nutrition and health outcomes.

Strengths and limitations

This review is strengthened by the adherence to the PRISMA, Cochrane and SWiM guidelines throughout. Another strength of this systematic review is the inclusion of a wide variety of studies and using a range of intervention methods and outcomes. This provided a broad overview of the way in which behavioural functions may increase effectiveness of nutrition interventions to improve maternal and child nutrition outcomes in sub-Saharan Africa. A limitation is the potential publication bias where studies mainly report on significant results which may not provide the full picture of what interventions work and which do not. One limitation was that breastfeeding interventions were excluded. This was due to previous systematic reviews finding limited evidence of behaviour change components in the interventions [33, 34]. One weakness of the review is that mainly papers written and published in English were reviewed. Another is that not all authors of these papers explicitly identified behaviour change functions in their descriptions of interventions, meaning that we may have missed other relevant papers. All titles, abstracts and full texts were double-screened against the inclusion and exclusion criteria, however, in order to minimise this possibility. Consistency in the types of data extracted and in judgements of the quality of the studies was ensured by having two independent reviewers review the included studies.

Compared to meta-analysis the synthesis method used provides more limited information for decision making. However, it is superior to only describing studies narratively. Vote counting based on direction of effect only answers the question “is there any evidence of an effect?”[39]. This method does not provide information on the magnitude of an effect and does not account for differences in the sample sizes of the included studies. Furthermore, the uncertainty of the results for the individual categories within the effect direction plot is high due to the small number of effects contributing to the analysis.


Improving nutritional outcomes requires behaviour change. To change nutrition behaviour, the COM-B model suggests that capability, opportunity and motivation should all be addressed [28]. Our analysis demonstrates that most nutrition-specific and nutrition-sensitive interventions only address participants’ capability and opportunities. Nutrition interventions therefore require the addition of behaviour change functions such as behaviour change communication and counselling to address participants’ automatic and reflective motivation. Automatic motivation is defined as the unconscious process that “energizes and directs behaviour” [28] (p4), including habits and emotional responses. Reflective motivation describes conscious processes such as analytical decision-making.

For example, one trial in Burkina Faso gave women land and seedlings (physical opportunity) and also had volunteers facilitate women’s groups using behaviour change communication that was empowering and motivating (automatic and reflective motivation [28]). Education functions of the communications in the trial in Burkina Faso may have changed the conscious decisions women were making about how to feed themselves and their children (reflective motivation) [57, 58]. The groups may have also created new social norms that encouraged women to change their dietary habits (automatic motivation).

This review linked three Behaviour Change Wheel intervention functions to improved nutrition and psychosocial outcomes. These were incentivisation, persuasion and environmental restructuring. All are hypothesised to change motivations [28]. Providing incentives, which include cash transfers and food vouchers, has been found to improve health outcomes. This could be because it increases household disposable income allowing families to spend more money on food [63, 118]. This is particularly significant in improving outcomes in the poorest communities. Another incentive used was nutritional supplements, which increased intervention attendance and uptake [65]. In contrast, failing to incentivise community health workers was given as a reason for their lack of motivation for delivering interventions [62]. Overall, there is compelling evidence that incentives can be a powerful motivating force in behaviour change interventions [122].

Persuasive communications were a common feature of many of the interventions in this review. These tended to focus on improving diet quality and diversity and were delivered through singing groups, storytelling and women’s groups. The Behaviour Change Wheel indicates that persuasion, because it is often emotive and induced positive or negative feelings, engages both reflective and automatic motivations [28]. This distinguishes it from purely educational communications which work by informing conscious decision-making (reflective motivation).

In one intervention that included persuasive communication, grandmothers were encouraged through nutrition education to promote improved nutritional practices related to pregnancy and infant feeding within their families [113]. This was delivered through songs, storytelling and group discussions and made an emotional appeal to grandmothers’ intrinsic commitment to family well-being. These persuasive communications were therefore explicitly designed to induce an emotional response (automatic motivation) as well as educate and inform (reflective motivation).

Environmental restructuring is the process of changing the physical and social environment, which is hypothesised to indirectly change motivation by cuing behaviour in a way which is often unconscious (automatic motivation). In the context of this review, environmental restructuring referred to provision of land, seedlings, livestock and equipment with the intention of increasing the effectiveness of community food production for both consumption and sale [57, 58, 66, 116]. It can be speculated that this provision addresses automatic motivations by increasing availability and diversity of food in these communities and supporting creation of new eating habits intended to improve diet quality.

Fig 4 illustrates the way in which all these intervention functions can be drawn together. Encouragingly, the addition of behaviour change functions to nutrition interventions may provide good value for money. An economic analysis within an intervention in Burundi calculated the relative cost of behaviour change functions accounted for approximately 13% of the budget whereas provision of food rations took up 30% [55]. Longitudinal studies are required to assess the impact of nutritional outcomes across children’s lifecourse and as communities undergo economic, nutritional, and societal transition [123].

Fig 4. Framework describing the way in which nutrition-specific and nutrition-sensitive interventions may be underpinned by behavioural concepts to improve maternal and child nutritional and psychosocial outcomes in sub-Saharan Africa.

(Adaption of Lassi et al, 2017 framework [124]).


This review indicates that nutrition-specific interventions, such as increasing access to food [20, 76], and nutrition-sensitive interventions, such as offering cash transfers [63] are not always enough to improve nutritional status of women and children in sub-Saharan Africa. Behaviour change communication and counselling are also unlikely on their own to be effective because they do not address food insecurity or nutritional deficiencies in high poverty contexts. Our findings indicate that interventions comprising all three Behaviour Change Wheel intervention functions (incentives, persuasion and environmental restructuring) were most likely to be effective in improving nutritional and psychosocial outcomes. By taking a health psychology perspective on this review, specifically drawing on concepts of automatic and reflective motivation from the Behaviour Change Wheel and COM-B model, motivation needs to be considered in designing an intervention to improve nutritional behaviour in the context of sub-Saharan Africa have been identified. To enhance the designs of these interventions, and ultimately improve the nutritional and psychosocial outcomes for mothers and infants in this region, multidisciplinary collaborations are required. Our recommendation would be to task behaviour change and nutrition experts such as health psychologists and nutritionists, as well as intervention designers, policy makers, and commissioners of services to fund and roll out these multicomponent behaviour change interventions.

Supporting information

S1 Table. Behaviour change systematic review search strategy.


S2 Table. Behaviour change systematic review screening document.


S3 Table. Behaviour Change Wheel (Michie et al, 2011).


S4 Table. Behaviour change systematic review quality assessment scoring rubric.


S5 Table. Behaviour change systematic review quality assessment form.



We would also like to thank the INPreP group for their contributions to this work: Engelbert A. Nonterah, Abraham Oduro, Cornelius Debpuur, James Adoctor, Paul Welaga, Edith Dambayi, Esmond W. Nonterah, Winfred Ofosu, Doreen Ayibisah, Maxwell Dalaba, Samuel Chatio (Navrongo Health Research Centre); Hermann Sorgho, Palwendé R. Boua, Adelaïde Compaoré, Kadija Ouedraogo, Karim Derra, Aminata Welgo, Halidou Tinto (Clinical Research Unit of Nanoro); Karen J. Hofman, Susan Goldstein, Agnes Erzse, Aviva Tugendhaft, Winfreda Mdewa, Ijeoma Edoka (SAMRC Centre for Health Economics and Decision Science, PRICELESS); Mark Hanson, Marie-Louise Newell, Keith M. Godfrey, Caroline Fall, Polly Hardy-Johnson (Faculty of Medicine, University of Southampton); Shane Norris, Emmanuel Cohen, Stephanie Wrottesley (SAMRC Developmental Pathways for Health Research Unit). We would also like to thank Paula Sands at the University of Southampton Health Sciences library for her support in developing the search strategy.


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